NumPy将8位转换为16/32位图像 [英] NumPy convert 8-bit to 16/32-bit image

问题描述

我正在使用OpenCV 2在YCbCr色彩空间中进行一些图像处理。目前我可以检测到由于转换RGB - > YCbCr然后YCbCr - > RGB引起的噪声，但如文档：

I am using OpenCV 2 to do some images manipulations in YCbCr color space. For the moment I can detect some noise due to the conversion RGB -> YCbCr and then YCbCr -> RGB, but as said in the documentation:

如果你使用带有8位图像的cvtColor，转换将会有一些信息丢失了。对于许多应用程序，这将不会引人注意，但建议在需要全范围颜色的应用程序中使用32位图像，或者在操作之前转换图像然后转换回来。

If you use cvtColor with 8-bit images, the conversion will have some information lost. For many applications, this will not be noticeable but it is recommended to use 32-bit images in applications that need the full range of colors or that convert an image before an operation and then convert back.

所以我想用16或32位转换我的图像，但我没有找到如何用NumPy做到这一点。一些想法？

So I would like to convert my image in 16 or 32 bits, but I didn't found how to do it with NumPy. Some ideas?

img = cv2.imread(imgNameIn)
# Here I want to convert img in 32 bits
cv2.cvtColor(img, cv2.COLOR_BGR2YCR_CB, img)
# Some image processing ...
cv2.cvtColor(img, cv2.COLOR_YCR_CB2BGR, img)
cv2.imwrite(imgNameOut, img, [cv2.cv.CV_IMWRITE_PNG_COMPRESSION, 0])

推荐答案

感谢@moarningsun，解决了问题：

Thanks to @moarningsun, problem resolved:

i = cv2.imread(imgNameIn, cv2.CV_LOAD_IMAGE_COLOR) # Need to be sure to have a 8-bit input
img = np.array(i, dtype=np.uint16) # This line only change the type, not values
img *= 256 # Now we get the good values in 16 bit format

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