Hands-On Image Processing with Python

Applying convolution to a color (RGB) image

With scipy.convolve2d(), we can sharpen an RGB image as well. We have to apply the convolution separately for each image channel.

Let's use the tajmahal.jpg image, with the emboss kernel and the schar edge detection complex kernel:

im = misc.imread('../images/tajmahal.jpg')/255 # scale each pixel value in [0,1]print(np.max(im))print(im.shape)emboss_kernel = np.array([[-2,-1,0],[-1,1,1],[0,1,2]])edge_schar_kernel = np.array([[ -3-3j, 0-10j, +3 -3j], [-10+0j, 0+ 0j, +10+0j], [ -3+3j, 0+10j, +3 +3j]])im_embossed = np.ones(im.shape)im_edges = np.ones(im.shape)for i in range(3):    im_embossed[...,i] = np.clip(signal.convolve2d(im[...,i], emboss_kernel, mode='same', boundary="symm"),0,1)for i in range(3): ...