![]() I guess I have 'discovered' something blatantly obvious - but in the non-brightened version, I think the leaves on the branch above the large bright spot in the bottom right have a reddish tint (reconstruct-lch-dt.jpg), while the naïve version (naive.jpg) looks (to my eyes) a tad more natural, even if I restore the correct camera matrix as input profile of the raw file (reconstruct-lch-with-camera-profile.jpg).Study of the highlight clipping using RawDigger histogram With exposure increased and filmic applied, the differences are perhaps even smaller ( and ). I loaded the raw into darktable, disabled all the non-linear modules (no filmic etc.), replaced the input colour profile with linear Rec2020 to match the other version and adjusted the exposure to match my naive development's result, and tried both clip and reconstruct modes in darktable's highlight reconstruction ( and ).įor the blown part, dt's clipping loses all details reconstruct-lch and my naive method seem to give comparable results. I then loaded this into darktable, and assigned linear Rec2020 as input profile (my tool does not support camera matrices), and exported the result -> The greying is done by simply averaging the RGB components. So, if a single pixel is blown, it will grey out both the RGB pixel located at the same coordinates, plus all 8 neighbours. finally, it greys out the pixels that are affected by any of the blown pixels (raw value > max value, taken from darktable's raw black/white level module).performs a simple demosaic by interpolating values from neighbouring pixels for the missing components (is that bilinear? I don't even know).applies the WB coefficients taken from darktable's WB module.applies the black and white points I took from darktable's raw black/white point module.I exported the raw data using dcraw -4 -W -T into a tiff file, and ran it through a tool I have started to code in order to understand raw development a bit more. ![]() ![]() I took a raw file that contains a large blown-out area. Sorry about the multiple updates - I'm quite tired and discovered a number of silly mistakes in the comment. I'm adding it here, although it's not about the raw over-exposure indicator, rather about what's clipped and what's not. Looking at the raw sensor data it seems that the green channels always saturate first, then red, and finally blue. Setting the indicators in darktable to 2.0 and reconstruct in Lch showed magenta in the areas where only the green channels were blown and raw overexposed in the areas where red, green, and sometimes blue were blown. I used the black and white levels from the raw file to determine what was clipped. I used dcraw to extract the sensor data, then octave to play with the individual channels. I took an image that showed raw overexposed areas. If you set the clipping threshold to 2.0 in the raw overexposed indicator and highlight reconstruction to 2.0 and reconstruct in Lch, then anything that shows as raw overexposed is blown in 3 (2 greens and something else) or more channels and anything showing in magenta is blown in 1 channel. So while sensor clipped = raw overexposed, raw overexposed != sensor clipped.Ĭan you use the raw overexposed indicator to figure out if the sensor clipped? I believe so. I think I've discovered the problem with the raw overexposure indicator.
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