On 01/-10/-28163 02:59 PM, kafooster wrote:
On 15 Cze, 01:25, Dave Angel<da...@ieee.org> wrote:
On 01/-10/-28163 02:59 PM, kafooster wrote:
On 14 Cze, 22:26, MRAB<pyt...@mrabarnett.plus.com> wrote:
Multiply the numpy array by a scaling factor, which is
float(max_8bit_value) / float(max_16bit_value).
could you please explain it a little? I dont understand it. like
multiplying each element?
You said in an earlier message to ignore the RAW format. However, if
your file matches a typical camera's raw file, there are several problems:
1) the data is typically 12 to 14 bits per pixel, only rarely 16 (very
expensive cameras)
2) the data does not have R, G and B values for each pixel, but only one
of these. The others are generated by Bayer interpolation.
3) the data is linear (which is what the hardware produces), and
traditional image data wants to be in some non-linear color space. For
example, most jpegs are sRGB 8*3 bits per pixel.
The first would mean that you'd need to do a lot of shifting and
masking. The second would mean a pretty complex interpolation
algorithm. And the third would require an exponential function at the
very least.
DaveA
well, I am only working with grayscale MRI medical images(mainly 8 or
16bits), saved as .raw. I do not need to worry about rgb.
Well, since you've already gotten results you like (per another msg from
you), the gamma adjustment must already be made. So they're an entirely
different meaning of raw than used by DSLR's, for example.
Glad it's working for you.
DaveA
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