My goal ultimately is to convert a .cr3-image to an RGB-array that i can seamlessly pass to an existing python-program. For the C++ to Python-interface i'm using pybind11.

The workhorse-function currently has the basic structure:

Using the -b option to adjust the brightness of the output image increases the color saturation for any brightness > 1. This is particularly noticeable for large brightness values (e.g. 16) for which the colors start looking entirely unrealistic. A benchmark comparison can be done by doing the exposure adjustment in Photoshop (Camera Raw) or Lightroom instead. Is the underlying algorithm flawed or does the -b option need to get used in conjunction with some other setting ?

I am processing an image from an X-Trans sensor (not a normal CFA). If I set user_mul to {1.0, 1.0, 1.0, 1.0} shouldn't the code use these values as the WB co-efficients, or did I miss something else I need to set to make the code use a user defined WB?

Certainly the output image appears identical to the daylight WB case.

Thanks
David

Hi All,

I am using LibRaw to decode raw files from Cannon and Nikon DSLR cameras. My code example currently looks like this:

Hi!

I found the 100 MP sensor is included in LibRaw supported camera list but for different camera models from Phase One. I was working with Phase One iXG 100 MP, and thought give a try how the output look like after default demosaicing. The output is more greenish (which is not correct) in output tiff ( dcraw_emu -v -dcbe -T input.IIQ ).

Any good suggestion on this unsupported camera issue? I have attached the output.