This is a long shot and i havent investigated it deeply, but this is what works and doesn't work:
The 40MP files are Nikon D800's, the 80MP is an PhaseOne IIQ.
16.2:
80 megapixel image + OpenMP = OK
17.0:
40 megapixel image +OpenMP = OK
80 megapixel image +Openmp = NOT OK, image has vertical stripes, takes ages to process and looks utterly corrupt
80 megapixel image (no openmp) = OK
Hi, i have a general question I've been pondering about. There are two noise reduction/denoising algorithms used in ACR, one is some luminance vawelet denoising algorithm and the second one I don't know much about is used for color artifacts. What algorithms do you think are used in the software?
I am using LibRaw to decode raw images and modify the raw pixel values. I am comparing the raw pixels (no processing applied in my code) to the 'raw' pixels from the same image after conversion to DNG format using Adobe's DNG Converter. I am accessing the raw pixels by calling LibRaw::open_file() -> LibRaw::unpack() -> LibRaw::raw2image(), and then accessing the pixel values in the imgdata.image structure.
There's something I cannot understand: when extracting the maximum value in the raw image, I obtain a small value whatever the camera used (Nikon D90 or PhaseOne IQ180).
Here is a piece of code to better understand my query:
I just downloaded and compiled the libraw APIs. I was trying to use the APIs to access the Raw bayer stream from a canon CR2 file.
After instantiating a LibRaw object and calling its open_file(), unpack() and raw2image() functions, im able to print out pixel values using the imgdata.image[pixelindex][channelindex] data array. (I see a nice RGBG pattern coming out here)
One of the images that I accessed had no values in the imgdata.color.cam_xyz array. All of them are 0.
My question is that, in absence of values of xyz to rgb conversion matrix, how do I do color correction?
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