Answer : You probably want to use an image's convert method: import PIL.Image rgba_image = PIL.Image.open(path_to_image) rgb_image = rgba_image.convert('RGB') In case of numpy array, I use this solution: def rgba2rgb( rgba, background=(255,255,255) ): row, col, ch = rgba.shape if ch == 3: return rgba assert ch == 4, 'RGBA image has 4 channels.' rgb = np.zeros( (row, col, 3), dtype='float32' ) r, g, b, a = rgba[:,:,0], rgba[:,:,1], rgba[:,:,2], rgba[:,:,3] a = np.asarray( a, dtype='float32' ) / 255.0 R, G, B = background rgb[:,:,0] = r * a + (1.0 - a) * R rgb[:,:,1] = g * a + (1.0 - a) * G rgb[:,:,2] = b * a + (1.0 - a) * B return np.asarray( rgb, dtype='uint8' ) in which the argument rgba is a numpy array of type uint8 with 4 channels. The output is a numpy array with 3 channels of type uint8 . This array is easy to do I/O with library imageio using imread and imsave .