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Everything posted by tupp

  1. Yes, and I have repeated those same points many times prior in this discussion. I was the one who linked the section in Yedlin's video that mentions viewing distances and viewing angles, and I repeatedly noted that he dismissed wider viewing angles and larger screens. How do you figure that I missed Yedlin's point in that regard? Not sure what you mean here nor why anyone would ever need to test "actual" resolution. The "actual" resolution is automatically the "actual" resolution, so there is no need to test it to determine if it is "actual". Regardless, I have used the term "discernability" frequently enough in this discussion so that even someone suffering from chronic reading comprehension deficit should realize that I am thoroughly aware that Yedlin is (supposedly) testing differences perceived from different resolutions. Again, Yedlin is "actually" comparing scaling methods with a corrupt setup. Not sure how 1-to-1 pixels can be interpreted in any way other than every single pixel of the tested resolution matches every single pixel on the screen of the person viewing the comparison. Furthermore, Yedlin was specific and emphatic on this point: Emphasis is Yedlin's. It's interesting that this basic, fundamental premise of Yedlin's comparison was misunderstood by the one who insisted that I must watch the entire video to understand it -- while I only had to watch a few minutes at the beginning of the video to realize that Yedlin had not achieved the required 1-to-1 pixel match. It makes perfect sense that 1-to-1 pixels means that every single pixel on the test image matches every single picture on one's display -- that condition is crucial for a resolution test to be valid. If the pixels are blended or otherwise corrupted, then the resolution test (which automatically considers how someone perceives those pixels) is worthless. It's obvious, and, unfortunately, it ruins Yedlin's comparisons. Well, I didn't compare the exact same frames, and it is unlikely that you viewed the same frames if you froze the video in Quicktime and VLC. When I play the video of Yedlin's frozen frame while zoomed-in on the Natron viewer, there are noticeable dancing artifacts that momentarily change the pixel colors a bit. However, since they repeat an identical pattern every time that I play the same moment in the video, it is likely those artifacts are inherent in Yedlin's render. Furthermore, blending is indicated as the general color and shade of the square's pixels and of those pixels immediately adjacent have less contrast with each other. In addition, the mottled pixel pattern of square and it's nearby pixels in the ffmpeg image generally matches the pixel pattern of those in the Natron image, while both images are unlike the drawn sqaure in Yedlin's zoomed-in viewer which is very smooth and precise. When viewing the square with a magnifier on the display, it certainly looks like its edges are blended -- just like the non-integer rulings on the pixel chart in my previous post. I suspect that Yedlin's node editor viewer is blending the pixels, even though it is set to 100%. Again, Yedlin easily could have provided verification of a 1-to-1 pixel match by showing a pixel chart in his viewer, but he didn't. ... and who's fault is that? Then perhaps Yedlin shouldn't misinform his easily impressionable followers by making the false claim that he has achieved a 1-to-1 pixel match on his followers' displays. On the other hand, Yedlin could have additionally made short, uncompressed clips of such comparisons, or he could have provided uncompressed still frames -- but he did neither. It really is not that difficult to create uncompressed short clips or stills with a 1-to-1 pixel match, just as it was done in the pixel charts above. I am arguing that his resolution test is invalid primarily because he is actually comparing scaling methods and even that comparison is rendered invalid by the fact that he did not show a 1-to-1 pixel match. In regards to Yedlin's and your dismissal of wider viewing angles because they are not common (nor recommended by SMPTE 🙄), again, such a notion reveals bias and should not be considered in any empirical tests designed to determine discernability/quality differences between different resolutions. A larger viewing angle is an important, valuable variable that cannot be ignored -- that's why Yedlin mentioned it (but immediately dismissed it as "not common"). Not that it matters, but there are many folks with multi-monitor setups that yield wider viewing angles than what you and Yedlin tout as "common." Also, again, there are a lot of folks that can see the individual pixels on their monitors, and increasing the resolution can render individual pixels not discernible. Have you also forgotten about RGB striped sensors, RGBW sensors, Foveon sensors, monochrome sensors, X-Trans sensors and linear scanning sensors? None of those sensors have a Bayer matrix. It matters when trying to make a valid comparison of different resolutions. Also, achieving a 1-to-1 pixel match and controlling other variables is not that difficult, but one must first fundamentally understand the subject that one is testing. Nope. I am arguing that Yedlin's ill-conceived resolution comparison with all of its wild, uncontrolled variables is not valid. That's not a bad reason to argue for higher resolution, but I doubt that it is the primary reason that Arri made a 6K camera. I can't wait to get a Nikon, Canon, Olympus or Fuji TV! Cropping is a valid reason for higher resolution (but I abhor the practice). My guess is that Arri decided to make a 6K camera because the technology exists, because producers were already spec'ing Arri's higher-res competition and because they wanted to add another reason to attract shooters to their larger format Alexa. Perhaps you should confront Yedlin with that notion, because it is with Yedlin that you are now arguing. As linked and quoted above, Yedlin thought that it was relevant to establish a 1-to-1 pixel match, and to provide a lengthy explanation in that regard. Furthermore, at the 04:15 mark in the same video, Yedlin adds that a 1-to-1 pixel match: Emphasis is Yedlin's. The point of a resolution discernability comparison (and other empirical tests) is to eliminate/control all variables except for the ones that are being compared. The calibration and image processing of home TVs and/or theater projectors is a whole other topic of discussion that needn't (and shouldn't) influence the testing of the single independent variable of differing resolution. If you don't think that it matters to establish a 1-to-1 pixel match in such a test, then please take up that issue with Yedlin -- who evidently disagrees with you!
  2. Keep in mind that resolution is important to color depth. When we chroma subsample to 4:2:0 (as likely with your A7SII example), we throw away chroma resolution and thus, reduce color depth. Of course, compression also kills a lot of the image quality. Yedlin also used the term "resolute" in his video. I am not sure that it means what you and Yedlin think it means. It is impossible for you (the viewer of Yedlin's video) to see 1:1 pixels (as I will demonstrate), and it is very possible that Yedlin is not viewing the pixels 1:1 in his viewer. Merely zooming "2X" does not guarantee that he nor we are seeing 1:1 pixels. That is a faulty assumption. Well, it's a little more complex than that. The size of the pixels that you see is always the size of the the pixels of your display, unless, of course, the zoom is sufficient to render the image pixels larger than the display pixels. Furthermore, blending and/or interpolation of pixels is suffered if the image pixels do not match 1:1 those of the display, or if the size image pixels are larger than those of the display while not being a mathematical square of the display pixels. Unfortunately, all of images that Yedlin presents as 1:1 most definitely are not a 1:1 match, with the pixels corrupted by blending/interpolation (and possibly compression). When Yedlin zooms-in, we see a 1:1 pixel match between the two images, so there is no actual difference in resolution in that instance -- an actual resolution difference is not being compared here nor in most of the subsequent "1:1" comparisons. What is being compared in such a scenario is merely scaling algorithms/techniques. However, any differences even in those algorithms get hopelessly muddled due to the fact that the pixels that you (and possibly Yedlin) see are not actually a 1:1 match, and are thus additionally blended and interpolated. Such muddling destroys any possibility of making a true resolution comparison. No. Such a notion is erroneous as the comparison method is inherently faulty and as the image "pipeline" Yedlin used unfortunately is leaky and septic (as I will show). Again, if one is to conduct a proper resolution comparison, the pixels from the original camera image should never be blended: an 8K captured image should be viewed on an 8K monitor; a 6K captured image should be viewed on an 6K monitor; a 4K captured image should be viewed on an 4K monitor; 2K captured image should be viewed on an 2K monitor; etc. Scaling algorithms, interpolations and blending of the pixels corrupts the testing process. I thought that I made it clear in my previous post. However, I will paraphrase it so that you might understand what is actually going on: There is no possible way that you ( @kye ) can observe the comparisons with a 1:1 pixel match to those of the images shown in Yedlin's node editor viewer. In addition, it is very possible that even Yedlin's own viewer when set at 100% is not actually showing a 1:1 pixel match to Yedlin. Such a pixel mismatch is a fatal flaw when trying to compare resolutions. Yedlin claims that he established a 1:1 match, because he knows that it is an important requirement for comparing resolutions, but he did not acheive a 1:1 pixel match. So, almost everything about his comparisons is meaningless. Again, Yedlin is not actually comparing resolutions in this instance. He is merely comparing scaling algorithms and interpolations here and elsewhere in his video, scaling comparisons which are crippled by his failure to achieve a 1:1 pixel match in the video. Yedlin could have verified a 1:1 pixel match by showing a pixel chart within his viewer when it was set to 100%. Here are a couple of pixel charts: If the the charts are displayed at 1:1 pixels, you should easily observe with a magnifier that the all of the black pixel rulings that are integers (1, 2, 3, etc.) are cleanly defined with no blending into adjacent pixels. On the other hand, all of the black pixel rulings that are non-integers (1.3, 1.6, 2.1, 2.4, 3.3, etc.) should show blending on their edges with a 1:1 match. Without such a chart it is difficult to confirm that one pixel of the image coincides with one pixel in Yedlin's video. Either Steve Yedlin, ASC was not savvy enough to include the fundamental verification of a pixel chart or he intentionally avoided verification of a pixel match. However, Yedlin unwittingly provided something that proves his failure to achieve a 1:1 match. At 15:03 in the video, Yedlin zooms way in to a frozen frame, and he draws a precise 4x4 pixel square over the image. At the 16:11 mark in the video, he zooms back out to the 100% setting in his viewer, showing the box at the alleged 1:1 pixels You can freeze the video at that point and see for yourself with a magnifier that the precise 4x4 pixel square has blended edges (unlike the clean-edged integer rulings on the pixel charts). However, Yedlin claims there is a 1:1 pixel match! I went even further than just using magnifier. I zoomed-in to that "1:1" frame using two different methods, and then I made a side-by-side comparison image: All three images in the above comparison were taken from the actual video posted on Yedlin's site. The far left image shows Yedlin's viewer fully zoomed-in when he draws the precise 4x4 pixel square. The middle and right images are zoomed into Yedlin's viewer when it is set to 100% (with an allegedly 1:1 pixel match). There is no denying the excessive blending and interpolation revealed when zooming-in to the square or when magnifying one's display. No matter how finely one can change the zoom amount in one's video player, one will never be able to see a 1:1 pixel match with Yedlin's video, because the blending/interpolation is inherent in the video. Furthermore, the blending/interpolation is possibly introduced by Yedlin's node editor viewer when it is set to 100%. Hence, Yedlin's claimed 1:1 pixel match is false. By the way, in my comparison photo above, the middle image is from a tiff created by ffmpeg, to avoid further compression. The right image was made by merely zooming into the frozen frame playing on the viewer of the Natron compositor. Correct. That is what I have stated repeatedly. The thing is, he uses this same method in almost every comparison, so he is merely comparing scaling methods throughout the video -- he is not comparing actual resolution. What? Of course there are such "pipelines." One can shoot with a 4K camera and process the resulting 4K files in post and then display in 4K, and the resolution never increases nor decreases at any point in the process. Are you trying to validate Yedlin's upscaling/downscaling based on semantics? It is generally accepted that a photosite on a sensor is a single microscopic receptor often filtered with a single color. A combination of more than one adjacent receptors with red, green, blue (and sometimes clear) filters is often called a pixel or pixel group. Likewise, an adjacent combination of RGB display cells is usually called a pixel. However you choose to define the terms or to group the receptors/pixels, it will have little bearing on the principles that we are discussing. Huh? What do you mean here? How do you get those color value numbers from 4K? Are you saying that all cameras are under-sampling compared to image processing and displays? Regardless of how the camera resolution is defined, one can create a camera image and then process that image in post and then display the image all without any increase nor decrease of the resolution at any step in the process. In fact, such image processing with consistent resolution at each step is quite common. It's called debayering... except when it isn't. There is no debayering with: an RGB striped sensor; an RGBW sensor; a monochrome sensor; a scanning sensor; a Foveon sensor; an X-Trans sensor; and three-chip cameras; etc. Additionally, raw files made with a Bayer matrix sensor are not debayered. I see where this is going, and your argument is simply a matter of whether we agree to determine resolution by counting the separate red, green and blue cells or whether we determine resolution by counting RGB pixel groups formed by combining those adjacent red, green and blue scales. Jeez Louise... did you just recently learn about debayering algorithms? The conversion of adjacent photosites into a single RGB pixel group (Bayer or not) isn't considered "scaling" by most. Even if you define it as such, that notion is irrelevant to our discussion -- we necessarily have to assume that a digital camera's resolution is given by either the output of it's ADC or by the resolution of the camera files. We just have to agree on whether we are counting the individual color cells or the combined RGB pixel groups. Once we agree upon the camera resolution, that resolution need never change throughout the rest of the "imaging pipeline." You probably shouldn't have emphasized that point, because you are incorrect, even if we use your definition of "scaling." There are no adjacent red green or blue photosites to combine ("scale") with digital Foveon sensors, digital three chip cameras and digital monochrome sensors. Please, I doubt that even Yedlin would go along with you on this line of reasoning. We can determine the camera resolution merely from output of the ADC or from the camera files. We just have to agree on whether we are counting the individual color cells or the combined RGB pixel groups. After we agree on the camera resolution, that resolution need never change throughout the rest of the "imaging pipeline." Regardless of these semantics, Yedlin is just comparing scaling methods and not actual resolution. When one is trying to determine if higher resolutions can yield an increase in discernability or in perceptible image quality, then it is irrelevant to consider the statistics of common or uncommon setups. The alleged commonality and feasibility of the setup is a topic that should be left for another discussion, and such notions should not influence nor interfere with any scientific testing nor with the weight of any findings of the tests. By dismissing greater viewing angles as uncommon, Yedlin reveals his bias. Such dismissiveness of important variables corrupts his comparisons and conclusions, as he avoids testing larger viewing angles, and he merely concludes that larger screens are "special". Well if I had a 4K monitor, I imagine that I could tell the difference between a 4K and 2K image. Not that it matters, but close viewing proximity is likely much more common than Yedlin realizes and more more common than your web searching shows. In addition to IMAX screens, movie theaters with seats close to the screen, amusement park displays and jumbo-trons, many folks position their computer monitors close enough to see the individual pixels (at least when they lean forward). If one can see individual pixels, a higher resolution monitor of the same size can make those individual pixels "disappear." So, higher resolution can yield a dramatic difference in discernability, even in common everyday scenarios. Furthermore, a higher resolution monitor with the same size pixels as a lower resolution monitor gives a much more expansive viewing angle. As many folks use multiple computer monitors side-by-side, the value of such a wide view is significant. Whatever. You can claim that combining adjacent colored photosites into a single RGB pixel group is "scaling." Nevertheless, the resolution need never change at any point in the "imaging pipeline." Regardless, Yedlin is merely comparing scaling methods and not resolution. Well, we can't really draw such a conclusion from Yedlin's test, considering all of the corruption from blending and interpolation caused by his failure to achieve a 1:1 pixel match. How is this notion relevant or a recap? Your statistics and what you consider be likely or common in regards to viewing angles/proximity is irrelevant in determining the actual discernability differences between resolutions. Also, you and Yedlin dismiss sitting in the very front row of a movie theater. That impresses you? Not sure how that point is relevant (nor how it is a recap), but please ask yourself: if there is no difference in discernability between higher resolutions, why would Arri (the maker of some of the highest quality cinema cameras) offer a 6K camera? Yes, but such points don't shed light on any fundamental differences in the discernability of different resolutions. Also how is this notion a recap? You are incorrect and this notion is not a recap. Please note that my comments in an earlier post regarding Yedlin's dismissing wider viewing angles referred to and linked to a section at 0:55:27 in his 1:06:54 video. You only missed all of the points that I made above in this post and earlier posts. No, it's not clear. Yedlin's "resolution" comparisons are corrupted by the fact that the pixels are not a 1:1 match and by the fact that he is actually comparing scaling methods -- not resolution.
  3. Oh, that is such a profound story. I am sorry to hear that you lost your respect for Oprah. Certainly, there are some lengthy videos that cannot be criticized after merely knowing the premise, such as this 3-hour video that proves that the Earth is flat. It doesn't make any sense at the outset and it is rambling, but you have to watch the entire 2 hours and 55 minutes, because (as you described the Yedlin video in an earlier post) "the logic of it builds over the course of the video." Let me know what you think after you have watched the entire flat Earth video. Now, reading your story has moved me, so I watched the entire Yedlin video! Guess what? -- The video is still fatally flawed, and I found even more problems. Here are four of the videos main faults: Yedlin's setup doesn't prove anything conclusive in regards to perceptible differences between various higher resolutions, even if we assume that a cinema audience always views a projected 2K or 4K screen. Much of the required discernability for such a comparison is destroyed by his downscaling a 6K file to 4K (and also to 2K and then back up to 4K) within a node editor, while additionally rendering the viewer window to an HD video file. To properly make any such comparison, we must at least start with 6K footage from a 6K camera, 4K footage from a 4K camera, 2K footage from a 2K camera, etc. Yedlin's claim here that the node editor viewer's pixels match 1-to-1 to the pixels on the screen of those watching the video is obviously false. The pixels in his viewer window don't even match 1-to-1 the pixels of his rendered HD video. This pixel mismatch is a critical flaw that invalidates almost all of his demonstrations that follow. At one point, Yedlin compared the difference between 6K and 2K by showing the magnified individual pixels. This magnification revealed that the pixel size and pixel quantity did not change when he switched between resolutions, nor did the subject's size in the image. Thus, he isn't actually comparing different resolutions in much of the video -- if anything, he is comparing scaling methods. Yedlin glosses over the factor of screen size and viewing angle. He cites dubious statistics regarding common viewing angles which he uses to make the shaky conclusion that larger screens aren't needed. Additionally, he avoids consideration of the fact that larger screens are integral when considering resolution -- if an 8K screen and an HD screen have the same pixel size, at a given distance the 8k screen will occupy 16 times the area of the HD screen. That's a powerful fact regarding resolution, but Yedlin dismisses larger screens as "specialty thing," Now that I have watched the entire video and have fully understood everything that Yedlin was trying to convey, perhaps you could counter the four problems of Yedlin's video listed directly above. I hope that you can do so, because, otherwise, I just wasted over an hour of my time that I cannot get back.
  4. The video's setup is flawed, and there are no parts in the video which explain how that setup could possibly work to show differences in actual resolution. If you disagree and if you think that you "understand" the video more than I, then you should have no trouble countering the three specific flaws of the video that I numbered above. However, I doubt that you actually understand the video nor the topic, as you can't even link to the points in the video that might explain how it works. I see. So, you have actually no clue about the topic, and you are just trolling.
  5. Good for you! Nope. The three points that I made prove that Yedlin's comparisons are invalid in regards to comparing the discernability of different resolutions. If you can explain exactly how he gets around those three problems, I will take back my criticism of Yedlin. So far, no one has given any explanation of how his set up could possibly work. Yes. I mentioned that section and linked it in a previous post. There is no way his set up can provide anything conclusive in regards to the lack of any discernability between different resolutions. He assumes that the 1-to-1 pixel view happens automatically, in a section that I linked in my previous post. Again, here is the link to that passage in Yedlin's video. It is impossible to get a 1-to-1 view of the pixels that appear within Yedlin's node editor -- those individual pixels were lost the moment he rendered the HD video. So, most of his comparisons are meaningless. No he doesn't show a 1-to-1 pixel view, because it is impossible to actually see the individual pixels within his node editor viewer. Those pixels were blended together when he rendered the HD video. In addition, even if Yedlin was able to achieve a 1-to-1 pixel match in his rendered video, the downscaling and/or downscaling and upscaling performed in the node editor destroys any discernable difference in resolutions. He is merely comparing scaling algorithms -- not actual resolution differences Furthermore, Yedlin reveals to us what is actually happening in many of his comparisons when we see the magnified view. The pixel size, the pixel number and the image framing all remain identical while he switches between different resolutions. So, again, Yedlin is not comparing different resolutions -- he is merely comparing scaling algorithms That is at the heart of what he is demonstrating. Yedlin is comparing the results of various downscaling and upscaling methods. He really isn't comparing different resolutions. Yedlin is not comparing different resolutions -- he is merely comparing scaling algorithms. You need to face that fact. Yedlin is a good shooter, but he is hardly an imaging scientist and he certainly is no pioneer. There are just too many flaws and uncontrolled variables in his comparisons to draw any reasonable conclusions. He covers the same ground and makes the same classic mistakes of others who have preceded him, so he doesn't really offer anything new. Furthermore, as @jcs pointed out, Yedlin's comparisons are "way too long and rambly." From what I have seen in these resolution videos and in his other comparisons, Yedlin glosses over inconvenient points that contradict his bias, and his methods are slipshot. In addition, I haven't noticed him contributing anything new to any of the topics which he addresses. Indeed... I don't think that Yedlin even understands his own tests. Well, I don't understand how a resolution comparison is valid if one doesn't actually compare different resolutions. You obviously cannot explained how such a comparison is possible. So, I am not going to risk wasting an hour of my time to watching more of a video comparison that is fatally flawed from the get-go.
  6. You are incorrect. Regardless, I have watched enough of the Yedlin videos to know that they are significantly flawed. I know for a fact that: Yedlin's setup cannot prove anything conclusive in regards to perceptible differences between various higher resolutions, even if we assume that a cinema audience always views a projected 2K or 4K screen. Much of the required discernability for such a comparison is destroyed by his downscaling a 6K file to 4K (and also to 2K and then back up to 4K) within a node editor, while additionally rendering the viewer window to an HD video file. To properly make any such comparison, we must at least start with 6K footage from a 6K camera, 4K footage from a 4K camera, 2K footage from a 2K camera, etc. Yedlin's claim here that the node editor viewer's pixels match 1-to-1 to the pixels on the screen of those watching the video is obviously false. The pixels in his viewer window don't even match 1-to-1 the pixels of his rendered HD video. This pixel mismatch is a critical flaw that invalidates almost all of his demonstrations that follow. At one point, Yedlin compared the difference between 6K and 2K by showing the magnified individual pixels. This magnification revealed that the pixel size and pixel quantity did not change when he switched between resolutions, nor did the subject's size in the image. Thus, he isn't actually comparing different resolutions in much of the video -- if anything, he is comparing scaling methods. In one of my earlier posts above, I provided a link to a the section of Yedlin's video in which he demonstrates the exact flaw that I criticized. Somehow, you missed the fact that what I claimed about the video is actually true. I also mentioned other particular problems of the video in my earlier posts, and you missed those points as well. So, no "straw man" here. As I have suggested in another thread, please learn some reading comprehension skills, so that I and others don't have to keep repeating ourselves. By the way, please note that directly above (within this post) is a numbered list in which I state flaws inherent in Yedlin's and please see that with each numbered point I include a link to the pertinent section of Yedlin's video. You can either address those points or not, but please don't keep claiming that I have not watched the video. In light of the fact that I actually linked portions of the video and made other comments about other parts of the video, logic dictates that I have at least watched those portions of the video. So, stating that I have not watched the video is illogical. Unless, of course, you missed those points in my post, in which case I would urge you once again to please develop your reading comprehension. Actually, neither you nor any other poster has directly addressed the flaws in Yedlin's video that I pointed out. If you think that I do not understand the videos, perhaps you could explain what is wrong with my specific points. You can start with the numbered list within this post.
  7. Agreed, but what is the point of all the downscaling and upscaling? What does it prove in regards to comparing the discernability of different resolutions? How can we compare different resolutions, if the differences in resolution are nullified at the outset of the comparison? In addition, is this downscaling and then upscaling something that is done in practice regularly? I have never heard of anyone intentionally doing so. Also, keep in mind that what Yedlin actually did was to downscale from 6K/4K to 2K, then upscale to 4K... and then downscale back to 1080. The delivered videos both on Yedlin's site and in your YouTube links are 1080. I honestly do not understand why anyone would expect to see much of a general difference after straight downscaling and then upscaling, especially when the results are rendered back down to HD. Please enlighten me on what is demonstrated by doing so. Furthermore, Yedlin merely runs an image through different scaling nodes in editing software while peering at the software's viewer, and I am not sure that doing so gives the same results as actually rendering an image to a lower resolution, then re-rendering it back to a higher resolution. Of course, there are numerous imaging considerations that transcend simple pixel counts. That issue has been examined endlessly on this forum and elsewhere, and I am not certain if Yedlin adds much to the discussion. By the way, my above quote from @jcs came from a 2-page "detail enhancement" thread on EOSHD. The inventive and original approach introduced within @jcs's opening post gives significant insight into sharpness/acuity properties that are more important than simple resolution. In that regard, the 1+ hour video on resolution by Steve Yedlin, ASC is far surpassed by just six short paragraphs penned by JCS, EOSHD.
  8. Then Tupp said that he didn't watch it, criticised it for doing things that it didn't actually do, then suggests that the testing methodology is false. Your interpretation of my interaction with your post here is certainly interesting. However, there is no need for interpretation, as one can merely scroll up to see my comments. Nevertheless, I would like to clarify a few things. Firstly, as I mentioned, I merely scanned the Yedlin videos for two reasons: I immediately encountered what are likely flaws in his comparisons (to which you refer as "things that it didn't actually do"); Yedlin's second resolution video is unnecessarily long and ponderous. Why should one waste time watching over an hour of long-winded comparisons that are dubious from the get go. Yedlin expects viewers to judge the differences in discernability between 6K, 4K and 2K footage rendered to full HD file on the viewers' own monitors. Also, we later see some of the footage downscaled to 2K and then upscaled to 4K. Unfortunately, even if we are able to view the HD file pixels at 1-to-1 on our monitors, most of the comparisons are still not valid. His zooming in and out while switching between downscaled/upscaled images is not equivalent to actually comparing 8K capture on an 8K monitor with 4k capture on a 4k monitor with 2K capture on a 2K monitor, etc. In regards to my claims of flaws in the video which are "things that it didn't actually do," here is the passage in the video that I mentioned in which the pixel size and pixel quantity did not change nor did the subject's size in the image. By the way, I disagree with his statement that the 2K image is less "resolute" than the 6K image when zoomed in. At that moment in the video, the 2K image looks sharper than the 6K image to me, both when zoomed in and zoomed out. So much for the flaws in the video "that it didn't actually do." As for the laborious length of some of Yedlin's presentations, I am not the only one here who holds that sentiment. Our own @jcs commented on the very resolution comparisons that we are discussing: Please note that this comment appeared in an informative thread about "Multi-spectral Detail Enhancement," acuity and sharpness, which is somewhat relevant to this thread regarding resolution. Nice comments! Thank you for your thoughtful consideration of my points!
  9. Thank you for the recommendation! I don't see any flaw in his strategy, but it also seems rather generic. Not sure if I should spend an hour watching a video that can be summed-up in a single sentence (as you just did). Also, I hesitate to watch a lengthy video that has fundamental problems inherent in its demonstrations (such as showing resolution differences without changing the pixel size nor pixel number).
  10. Very cool! Your rig reminds me of @ZEEK's EOSM Super 16 setup. It shoots 2.5K, 10-bit continuously or 2.8K, 10-bit continuously with ML at around 16mm and Super 16 frame sizes.
  11. We've certainly talked about resolution, and other Yedlin videos have been linked in this forum. I merely scanned the videos (that second video is over an hour in length), so I don't know all the points that he covered. Resolution and sharpness are not the same thing. There is a contrast element to sharpness, and it involves different levels (macro contrast micro contrast, etc.). One can see the effects of different levels of contrast when doing frequency separation work in images. Not sure if Yedlin specifically covers contrast's relation to sharpness in these videos. By the way, here is a recent demonstration of when micro features and macro features don't match. Also, I am not sure that his resolution demo is valid, as he seems to be showing different resolutions on the same monitor. I noticed in one passage that he was zoomed in to see individual pixels, and, when switching between resolutions, the pixel size and pixel quantity did not change nor did the subject's size in the image. Something is wrong with that comparison. To properly demonstrate resolution differences in regards to discernible detail, one really must show a 6K-captured image on a 6K monitor, a 4K-captured image on a 4K monitor and an HD/2K captured image on an HD/2K monitor, etc. -- and all monitors must be the same size and and same distance from the viewer. The only other demonstration that I have seen by Yedlin also had significant flaws. Furthermore, there are other considerations, such as how resolution influences color depth and how higher resolution can help transcend conversion/algorithmic losses and how higher resolution allows for cropping, etc. There are problems with the few Yedlin videos that I have seen. Also, one of his videos linked above is lengthy and somewhat ponderous. I would put the Panavision Genesis (and it's little brother, the Sony F35) up against an Alexa any day, and the Genesis has lower resolution and less dynamic range than the Alexa. However, the Genesis has a lush, striped, RGB, CCD with true HD -- 1920x1080 RGB pixel groups. Similarly, I recall that the Dalsa Origin demos showed a thick image (it shot 16-bit, 4K), and the Thompson Viper HD CCD camera yielded great footage. I certainly agree that there is a threshold beyond which higher resolution generally is not necessary in most cases, and I think that that such a threshold has been mentioned a few times in this forum. On the other hand, I don't think that such a threshold is absolute, as so much of imaging is subjective and a lot of SD productions are still very compelling today. I have shot a fair amount of film, but I would not say that the image quality of film is "better." It's easier (and more forgiving) to shoot film in some ways, but video is easier in many other ways and it can give a great image. Exactly.
  12. tupp


    This is a good suggestion. A snorkel bag is usually very thick plastic/vinyl. Just substitute taped foam pads for socks!
  13. tupp


    If you wrap your rain cover properly, you shouldn't have to worry about paint getting in. In regards to the impact, I don't know anything about the force of paint ball guns. If you don't use an insulated (padded) rain cover, you could tape pieces of foam sheet onto vulnerable areas on the camera and then put on the rain cover/bag. You could also run some impact tests with a paint gun, rain cover, foam pads and a wine glass.
  14. tupp


    Use the Glidecam with a rain cover and keep all flaps on the rain cover tucked-in (or use tape). Should be okay. Another option is to use a heavy, clear freezer bag around the camera, with the opening taped to the lens hood.
  15. tupp


    When you said "Glidecam," I got the impression that you were using a Steadicam type rig -- not an electronic gimbal. Furthermore, a solid underwater housing might be too much for a gimbal.
  16. tupp


    An underwater housing seems like overkill for your purpose. A rain cover and a strong lens filter might be better and easier. If you are concerned about damage from the impact force of the paint balls, you could try an insulated rain cover.
  17. Nope. I said "A conversion can be made so that the resulting Full HD 10-bit image has essentially the equivalent color depth as the original 4K 8-bit image." I didn't say anything about the original image having "reduced" color depth. You came up with that. However, the original image does have lower bit depth than the down-converted image -- even though both images have the same color depth. Yes. That is a fact -- all other variables being the same in both instances. No. It doesn't disagree with anything that I have said. You are just confusing bit depth with color depth. With such a down-conversion, resolution is being swapped for greater bit depth -- but the color depth remains the same in both images. It really is simple, and Andrew Reid's article linked above verifies and explains the down-conversion process. No. The banding artifact is caused by the bit depth -- not by the color depth. Posterization, bit depth and color depth are all different properties. Well, it would be so if bit depth and color depth were the same thing, but they're not. Stop confusing bit depth with color depth. I linked an article by the founder of this forum that verifies from a prominent image processing expert that one can swap resolution for higher bit depth when down-converting images -- while retaining the same amount of color information (color depth): Also, that very article gives a link to the expert's Twitter feed, should you care to verify that the down-conversion process is actually a fact. Furthermore, I have given an example proving that resolution affects color depth, and you even agreed that it was correct: Additionally, I gave lead-pipe cinch demonstration on how increasing pixel sites within a given area creates more possible shades, to which you did not directly respond. Do you deny the facts of that demonstration? I have repeated essentially the same thing over and over. It is you who keeps lapsing into confusion between color depth and bit depth. I have paraphrased the concept repeatedly in different forms, and I have given examples that clearly demonstrate that resolution is integral to color/tone depth. In addition, I have linked an article from the forum founder that further explains the concept and how it can work in a practical application. If you don't understand the simple concept by now, than I am not sure there is much more that I can do. Wait, I thought that you said: I never asserted that "resolution can increase bit-depth." Please quit putting words into my mouth. Changing the resolution will have no effect on the bit depth nor vice versa -- resolution and bit depth are two independent properties. On the other hand, resolution and bit depth are the two non-perceptual factors of color depth. So, if the resolution is increased, the color depth is increased (as exemplified in halftone printing and in my pixel site example). Likewise, if the bit depth is increased, the color depth is increased. Banding/posterization is something completely different. It is an phenomenon that can occur with lower bit depths in some situations, but it also can occur in analog imaging systems that possess neither bit depth nor pixels. The color depth of an image is not affected by whether or not the image exhibits posterization. Let's say that you shoot two 4k, 8-bit images of the sky within the same few seconds: one which is aimed at a part of the sky that exhibits no banding and one which is aimed at a portion of the sky produces banding. Then, you down-convert both images to Full HD, 10-bit using the method described in Andrew Reid's article in which no color information is lost from the original images. Would you say that the Full HD, 10-bit image of the banded sky has less color depth than the Full HD 10-bit image of the smooth sky? Well, it's good that you are looking out for us. Now, if you could only avoid confusing bit depth and color depth...
  18. I sense irony here. A conversion can be made so that the resulting Full HD 10-bit image has essentially the equivalent color depth as the original 4K 8-bit image. Of course, there are slight conversion losses/discrepancies. The banding remains because it is an artifact that is inherent in the original image. That artifact has nothing to do with the color depth of the resulting image -- the banding artifact in this case is caused merely by a lower bit depth failing to properly render a subtle transition. However, do not forget that bit depth is not color depth -- bit depth is just one factor of color depth. It's actually very simple. I never claimed that the banding would get eliminated in a straight down-conversion. In fact, I made this statement regarding your scenario of a straight down-conversion from an 8K banded image to an SD image: Where did you get the idea that I said banding would get eliminated in a straight conversion. You have to grasp the difference between banding/posteriztion artifacts and the color depth of an image.
  19. If you (and/or your client) like the aspect ratio and like the fact that you are using a wider portion of the image circle of your lenses, then, to me, those are the most important considerations. So, you are probably best shooting at 4096x2160 (DCI 4K) and down-converting cleanly to 2048x1080 (DCI 2K) or less cleanly to 1920x1013. Any extra rendering time for the odd height pixel in the "less clean" resolution would likely be minimal, but it would probably be a good idea to test it, just to make sure.
  20. Glad to know that I am making progress. You have not directly addressed most of my points, which suggests that you agree with them. Firstly, the banding doesn't have to be eliminated in the down conversion to retain the full color depth of the original image. Banding/posterization is merely an artifact that does not reduce the color depth of an image. One can shoot a film with a hair in the gate or shoot a video with a dust speck on the sensor, yet the hair or dust speck does not reduce the image's color depth. Secondly, broad patches of uniformly colored pale sky tend to exhibit shallow colors that do not utilize a lot of color depth bandwidth. So, it's not as if there is much color depth lost in the areas of banding. Thirdly, having no experience with 8K cameras, I am not sure if the posterization threshold of such a high resolution behaves identically to those of lower resolutions. Is the line in the same place? Is it smooth or crooked or dappled? In regards to eliminating banding during a down conversion, there are many ways to do so. One common technique is selective dithering. I have read that diffusion dithering is considered most favorable over other dithering methods.
  21. Nope. Color depth is the number of different colors that can be produced in a given area. A given area has to be considered, because imaging necessarily involves area... which area necessarily involves resolution. Obviously, if a 1-bit imaging system produces more differing colors as the resolution is increased, then resolution is an important factor to color depth -- it is not just bit depth that determines color depth. The above example of a common screen printing is just such an imaging system that produces a greater number of differing colors as the resolution increases, while the bit depth remains at 1-bit. The Wikipedia definition of color depth is severely flawed in at least two ways: it doesn't account for resolution; and it doesn't account for color depth in analog imaging systems -- which possess absolutely no bit depth nor pixels. Now, let us consider the wording of the Wikipedia definition of color depth that you quoted. This definition actually gives two image areas for consideration "a single pixel" -- meaning an RGB pixel group; and "the number of bits used for each color component of a single pixel" -- meaning a single pixel site of one of the color channels. For simplicity's sake, let's just work with Wikipedia's area #2 -- a single channel pixel site of a given bit depth of "N." We will call the area of that pixel site "A." If we double the resolution, the number of pixel sites in "A" increases to two. Suddenly, we can produce more tones inside "A." In fact, area "A" can now produce "N²" number of tones -- much more than "N" tones. Likewise, if we quadruple the resolution, "A" suddenly contains four times the pixel sites that it did originally, with the number of possible tones within "A" now increasing to "N⁴." Now, one might say, "that's not how it actually works in digital images -- two or four adjacent pixels are not designed to render a single tone." Well, the fact is that there are some sensors and monitors that use more pixels within a pixel group than those found within the typical Bayer pixel group or found withing a striped RGB pixel group. Furthermore (and probably most importantly), image detail can feather off within one or two or three pixel groups, and such tiny transitions might be where higher tone/color depth is most utilized. By the way, I didn't come up with the idea that resolution is "half" of color depth. It is a fact that I learned when I studied color depth in analog photography in school -- back when there was no such thing as bit depth in imaging. In addition, experts have more recently shown that higher resolutions give more color information (color depth), allowing for conversions from 4k, 4:2:0, 8-bit to Full HD, 4:4:4, 10-bit -- using the full, true 10-bit gamut of tones. Here is Andrew Ried's article on the conversion and here is the corresponding EOSHD thread.
  22. Well, this scenario is somewhat problematic because one is using the same camera with the same sensor. So, automatically there is a binning and/or line-skipping variable. However, barring such issues and given that all other variables are identical in both instances, it is very possible that the 8K camera will exhibit a banding/posterization artifact just like the SD camera. Nevertheless, the 8K camera will have a ton more color depth than the SD camera, and, likewise, the 8K camera will have a lot more color depth than a 10-bit, 800x600 camera that doesn't exhibit the banding artifact. Of course, it is not practical to have 1-bit camera sensors (but it certainly is possible). Nonetheless, resolution and bit depth are equally weighted factors in regards to color depth in digital imaging, and, again, a 4k sensor has 4 times the color depth of an otherwise equivalent Full HD sensor.
  23. I acknowledged your single "complexity" (bit rate), and even other variables, including compression and unnamed natural and "artificial" influences such as A/D conversion methods, resolution/codec conversion methods, post image processing effects, etc. By the way, greater bit rate doesn't always mean superior images, even with all other variables (including compression) being the same. A file can have greater bit rate with a lot of the bandwidth unused and/or empty. One is entitled to one's opinion, but the fact is that resolution is integral to digital color depth. Furthermore, resolution has equal weighting to bit depth when one considers a single color channel -- that is a fundamental fact of digital imaging. Here is the formula: COLOR DEPTH = RESOLUTION X BITDEPTH^n (where "n" is the number of color channels and all where pixel groups can be discerned individually). Most don't realize it, but a 1-bit image can produce zillions of colors. We witness this fact whenever we see images screen printed in a magazine, on a poster or on a billboard. Almost all screen printed photos are 1-bit images made up of dots of ink. The ink dot is either there or it is not there (showing the white base) -- there are no "in-between" shades. To increase the color depth in such 1-bit images, one must increase the resolution by using a finer printing screen. That resolution/color-depth relationship of screen printing also applies to digital imaging (and also to analog imaging), even if the image has greater bit depth. I simply state fact, and the fact is that 4k has 4 times the color depth and 4 times the bit rate of full HD (all other variables being equal and barring compression, of course).
  24. 4K has 4 times the color depth (and 4 times the bit rate) of full HD, all other variables being equal and barring compression or any artificial effects.
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