Error in the handling of color: part IV, linear gamma | blog.lexa.ru
This is the fourth article on the subject of errors in color conversion, we are getting closer to real-world buffet golden corral problems. List of previous series: errors when working with 8-bit images (sRGB) error handling 16-bit data (sRGB) 16-bit data, BetaRGB gradually we come to the real problems ....
From experience we know that digital noise in the shadows most likely to occur in the processing of the data with a linear "range", and these are the images that we get from the line sensors: digital cameras and scanners. Let's see what happens with errors on the test cases. A full range of formulation of the problem is the same: 4096x4096 image containing 16 million colors, a series of processing: assign profile BetaRGB with gamma set to 1.0; convert to Lab; convert back to BetaRGB-gamma1; look pixel-difference histogram. Part of the colors of the source file does not fit within the scope of (gamut) Space Lab, so watch where it can be clipped and these pixels are not taken into account (described in detail in a previous publication, where you can take a test file and look at the example of a clipping mask). The participants of the race are the same: Adobe Photoshop CS3 (10.0.1) with three available CMM (Adobe, Apple, Microsoft) Argyll CMS 0.7 beta 7 LCMS 1.17 The result is shown in the histogram: The results are quite interesting Argyll: a clear leader. I'm still in the first text was expecting OpenSource udelaet commercial buffet golden corral software, wait. The result is better and average and maximum deviation. Adobe and Apple: the result is close, but Adobe is somewhat better, too, no questions asked. 3-4 bit errors for linear space - a lot, but you can live. LCMS showed nothing remarkable not never, here, too, does not stand out. Microsoft CMM has always been one of the worst in my tests, and stayed there. 12-bit data 12-bit linear data - this is what we have in real life with an average hand scanner or a digital camera with a good (to put 14-bit ADC started recently, and their meaning buffet golden corral is not obvious). Therefore, the result of processing such data is particularly interesting is the work of RAW-converters. In the race attended only three of which have shown themselves most reasonable: Apple, Adobe, Argyll (CMM nice words with the letter A?). Enjoying a histogram buffet golden corral of bit errors to be honest, look uncomfortable, so the same thing, but in a linear scale error: Results: Argyll: 307 pixels 16 million have an error in 1, all other error is zero; Adobe: 789 000 pixels with an error 2, the other with a zero; Apple: 42 kilopixels error 3, 2.86 million with an error of 2, and the rest - zero error. In general, 12-bit raw data error in the 2 units reduces the dynamic range from 12 to 10 stops, in other words, it's a BIG mistake. Conclusions open source taxis (I doubt that I would write these words about the software for image processing). If the data is sufficient to convert buffet golden corral the matrix profile, the Argyll - unequivocal buffet golden corral leader (from the fact that try). In real life, of course, are more commonly used table ... watch for announcements. Add new comment
Alexander, I did upon reading the question appeared on the evaluation. why you raschityvaete deviation in the space of the RSL. because this system neravnokontrastna why you did not find the deviation when converting lab-- RSL - lab? reply
whether _bolshaya_? So that the eye see on 8-bit monitor? Well take a real (portrait, buffet golden corral flower, etc) image, such as the actual process buffet golden corral in Photoshop with different CMM, and vizulno compare the resulting buffet golden corral images. reply
Here all the pain in the linear scale - noise in the shadows (of processing, for example) will be a) enhanced by the transition to the range of 2.2 b) if the picture was originally a large DD and want to save it (and leave a light and shadow), then either we will be local contrast buffet golden corral (well, at least shadow-highlight), which is still strengthen the noise in the shadows, or just reverse S-curve, which also will increase. reply
"Strengthen the noise in the shadows" ... Well, we have a useful point (10,10,10) and a number of spurious noise (1,1,1). buffet golden corral After tightening the shadows they have (20,20,20) and (2,2,2). Noise has become more visible, but signal / noise ratio remained the same? reply
In order. 1) This is not the only test. For the conversion of gamma 2.2 RGB-Lab- (editing) buffet golden corral -RGB has an obvious meaning. For gamma 1 - naturally normal situation is RGB (g1) -Lab (like PCS) -> RGB (gamma 2.2), but it does not work to compare the source and result.
4) noise. Here you had a signal, say 2,3,4 in three different pixels (the difference on the feet in a linear space). After conversion to become 10,12,14 (for simplicity, gamma 2), and therefore such 12,13,14 (digital noise +2, +1, 0). From the stop was polstopa. A "will strengthen the noise in the shadows" of some tul with local contrast, the same S / H reply Add new comment
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This is the fourth article on the subject of errors in color conversion, we are getting closer to real-world buffet golden corral problems. List of previous series: errors when working with 8-bit images (sRGB) error handling 16-bit data (sRGB) 16-bit data, BetaRGB gradually we come to the real problems ....
From experience we know that digital noise in the shadows most likely to occur in the processing of the data with a linear "range", and these are the images that we get from the line sensors: digital cameras and scanners. Let's see what happens with errors on the test cases. A full range of formulation of the problem is the same: 4096x4096 image containing 16 million colors, a series of processing: assign profile BetaRGB with gamma set to 1.0; convert to Lab; convert back to BetaRGB-gamma1; look pixel-difference histogram. Part of the colors of the source file does not fit within the scope of (gamut) Space Lab, so watch where it can be clipped and these pixels are not taken into account (described in detail in a previous publication, where you can take a test file and look at the example of a clipping mask). The participants of the race are the same: Adobe Photoshop CS3 (10.0.1) with three available CMM (Adobe, Apple, Microsoft) Argyll CMS 0.7 beta 7 LCMS 1.17 The result is shown in the histogram: The results are quite interesting Argyll: a clear leader. I'm still in the first text was expecting OpenSource udelaet commercial buffet golden corral software, wait. The result is better and average and maximum deviation. Adobe and Apple: the result is close, but Adobe is somewhat better, too, no questions asked. 3-4 bit errors for linear space - a lot, but you can live. LCMS showed nothing remarkable not never, here, too, does not stand out. Microsoft CMM has always been one of the worst in my tests, and stayed there. 12-bit data 12-bit linear data - this is what we have in real life with an average hand scanner or a digital camera with a good (to put 14-bit ADC started recently, and their meaning buffet golden corral is not obvious). Therefore, the result of processing such data is particularly interesting is the work of RAW-converters. In the race attended only three of which have shown themselves most reasonable: Apple, Adobe, Argyll (CMM nice words with the letter A?). Enjoying a histogram buffet golden corral of bit errors to be honest, look uncomfortable, so the same thing, but in a linear scale error: Results: Argyll: 307 pixels 16 million have an error in 1, all other error is zero; Adobe: 789 000 pixels with an error 2, the other with a zero; Apple: 42 kilopixels error 3, 2.86 million with an error of 2, and the rest - zero error. In general, 12-bit raw data error in the 2 units reduces the dynamic range from 12 to 10 stops, in other words, it's a BIG mistake. Conclusions open source taxis (I doubt that I would write these words about the software for image processing). If the data is sufficient to convert buffet golden corral the matrix profile, the Argyll - unequivocal buffet golden corral leader (from the fact that try). In real life, of course, are more commonly used table ... watch for announcements. Add new comment
Alexander, I did upon reading the question appeared on the evaluation. why you raschityvaete deviation in the space of the RSL. because this system neravnokontrastna why you did not find the deviation when converting lab-- RSL - lab? reply
whether _bolshaya_? So that the eye see on 8-bit monitor? Well take a real (portrait, buffet golden corral flower, etc) image, such as the actual process buffet golden corral in Photoshop with different CMM, and vizulno compare the resulting buffet golden corral images. reply
Here all the pain in the linear scale - noise in the shadows (of processing, for example) will be a) enhanced by the transition to the range of 2.2 b) if the picture was originally a large DD and want to save it (and leave a light and shadow), then either we will be local contrast buffet golden corral (well, at least shadow-highlight), which is still strengthen the noise in the shadows, or just reverse S-curve, which also will increase. reply
"Strengthen the noise in the shadows" ... Well, we have a useful point (10,10,10) and a number of spurious noise (1,1,1). buffet golden corral After tightening the shadows they have (20,20,20) and (2,2,2). Noise has become more visible, but signal / noise ratio remained the same? reply
In order. 1) This is not the only test. For the conversion of gamma 2.2 RGB-Lab- (editing) buffet golden corral -RGB has an obvious meaning. For gamma 1 - naturally normal situation is RGB (g1) -Lab (like PCS) -> RGB (gamma 2.2), but it does not work to compare the source and result.
4) noise. Here you had a signal, say 2,3,4 in three different pixels (the difference on the feet in a linear space). After conversion to become 10,12,14 (for simplicity, gamma 2), and therefore such 12,13,14 (digital noise +2, +1, 0). From the stop was polstopa. A "will strengthen the noise in the shadows" of some tul with local contrast, the same S / H reply Add new comment
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Plain text You can enable syntax highlighting of source code with the following tags: <code>, <blockcode>, <c>, <cpp>, <drupal5>, buffet golden corral <drupal
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