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. -- http://mail.python.org/mailman/listinfo/python-list
