5 ms·

https://i.imgur.com/CRq6Kn8.png https://i.imgur.com/CRq6Kn8.png (left: linear, right: sRGB) In linear interpolation, there's too much white and not enough blac

https://i.imgur.com/CRq6Kn8.png https://i.imgur.com/CRq6Kn8.png (left: linear, right: sRGB) In linear interpolation, there's too much white and not enough black. That's why gamma correction/sRGB exists after all: if you encode the linear value directly, you waste most of the space on white values you can barely tell apart.

orlp 5y ago
Sorry but this is just your example being horribly misgenerated/some gamma being applied twice, maybe even thrice. Here is what I generated: sRGB: https://i.imgur.com/dbn3TM6.png https://i.imgur.com/dbn3TM6.png Lab (linear): https://i.imgur.com/dCXzbF3.png https://i.imgur.com/dCXzbF3.png Please download the images and view in a proper image viewer. For some reason at least on my Windows machine Google Chrome adds horrible color banding to both images. This is my code: import imageio import numpy as np import colour quantize_with_dither = lambda im: np.clip(im * (2**8-1) + np.random.uniform(size=im.shape), 0, 2**8-1).astype(np.uint8) srgb_black = [0, 0, 0] srgb_white = [1, 1, 1] srgb_grad = np.linspace(srgb_black, srgb_white, 500) * np.ones((200, 1, 3)) imageio.imwrite("srgb.tif", quantize_with_dither(srgb_grad)) lab_black = colour.XYZ_to_Lab(colour.sRGB_to_XYZ(srgb_black)) lab_white = colour.XYZ_to_Lab(colour.sRGB_to_XYZ(srgb_white)) lab_grad = np.linspace(lab_black, lab_white, 500) * np.ones((200, 1, 3)) lab_grad_in_srgb = colour.XYZ_to_sRGB(colour.Lab_to_XYZ(lab_grad)) imageio.imwrite("lab.tif", quantize_with_dither(lab_grad_in_srgb)) I didn't trust imageio's correct handling of gamma/colorspaces so I just wrote out the raw sRGB coefficients as 8-bit TIFF and used imagemagick to convert to PNG, telling it that the input is in sRGB: magick convert lab.tif -set colorspace sRGB -depth 8 lab.png magick convert srgb.tif -set colorspace sRGB -depth 8 srgb.png
- kingcharles 5y ago
  That banding is odd. I get the same issue on Windows 11 latest Chrome build. Looks fine in Windows default image viewer. These are PNG images, so there is no decompression to mangle them. The only way the two images could differ is in the way the pixels are massaged into the color space. Weird.
- edflsafoiewq 5y ago
  Lab is not linear. L predicts perceptual brightness, just like sRGB, which is probably why your two gradients are almost the same. Gamma encoding is lin_to_srgb(c) = c*12.92 if c<=0.0031308 else 1.055*c**(1/2.4)-0.055. Since lin_to_srgb(0.214)=0.5, in a linear ramp, the middle gray (808080) pixel should occur about 20% of the way through.
echeese 5y ago
I've generated my own version of this (i just happened to be working on something that needed gamma correct rendering) https://i.imgur.com/jeM4RCu.png https://i.imgur.com/jeM4RCu.png top: linear_to_srgb(x) middle: x bottom: srgb_to_linear(x)

orlp 5y ago

Sorry but this is just your example being horribly misgenerated/some gamma being applied twice, maybe even thrice. Here is what I generated: sRGB: https://i.imgur.com/dbn3TM6.png https://i.imgur.com/dbn3TM6.png Lab (linear): https://i.imgur.com/dCXzbF3.png https://i.imgur.com/dCXzbF3.png Please download the images and view in a proper image viewer. For some reason at least on my Windows machine Google Chrome adds horrible color banding to both images. This is my code: import imageio import numpy as np import colour quantize_with_dither = lambda im: np.clip(im * (2**8-1) + np.random.uniform(size=im.shape), 0, 2**8-1).astype(np.uint8) srgb_black = [0, 0, 0] srgb_white = [1, 1, 1] srgb_grad = np.linspace(srgb_black, srgb_white, 500) * np.ones((200, 1, 3)) imageio.imwrite("srgb.tif", quantize_with_dither(srgb_grad)) lab_black = colour.XYZ_to_Lab(colour.sRGB_to_XYZ(srgb_black)) lab_white = colour.XYZ_to_Lab(colour.sRGB_to_XYZ(srgb_white)) lab_grad = np.linspace(lab_black, lab_white, 500) * np.ones((200, 1, 3)) lab_grad_in_srgb = colour.XYZ_to_sRGB(colour.Lab_to_XYZ(lab_grad)) imageio.imwrite("lab.tif", quantize_with_dither(lab_grad_in_srgb)) I didn't trust imageio's correct handling of gamma/colorspaces so I just wrote out the raw sRGB coefficients as 8-bit TIFF and used imagemagick to convert to PNG, telling it that the input is in sRGB: magick convert lab.tif -set colorspace sRGB -depth 8 lab.png magick convert srgb.tif -set colorspace sRGB -depth 8 srgb.png

kingcharles 5y ago
That banding is odd. I get the same issue on Windows 11 latest Chrome build. Looks fine in Windows default image viewer. These are PNG images, so there is no decompression to mangle them. The only way the two images could differ is in the way the pixels are massaged into the color space. Weird.
edflsafoiewq 5y ago
Lab is not linear. L predicts perceptual brightness, just like sRGB, which is probably why your two gradients are almost the same. Gamma encoding is lin_to_srgb(c) = c*12.92 if c<=0.0031308 else 1.055*c**(1/2.4)-0.055. Since lin_to_srgb(0.214)=0.5, in a linear ramp, the middle gray (808080) pixel should occur about 20% of the way through.

echeese 5y ago

I've generated my own version of this (i just happened to be working on something that needed gamma correct rendering) https://i.imgur.com/jeM4RCu.png https://i.imgur.com/jeM4RCu.png top: linear_to_srgb(x) middle: x bottom: srgb_to_linear(x)