clahe.py 文件源码

def enhance(image_path, clip_limit=3):
    image = cv2.imread(image_path)
    # convert image to LAB color model
    image_lab = cv2.cvtColor(image, cv2.COLOR_BGR2LAB)

    # split the image into L, A, and B channels
    l_channel, a_channel, b_channel = cv2.split(image_lab)

    # apply CLAHE to lightness channel
    clahe = cv2.createCLAHE(clipLimit=clip_limit, tileGridSize=(8, 8))
    cl = clahe.apply(l_channel)

    # merge the CLAHE enhanced L channel with the original A and B channel
    merged_channels = cv2.merge((cl, a_channel, b_channel))

    # convert iamge from LAB color model back to RGB color model
    final_image = cv2.cvtColor(merged_channels, cv2.COLOR_LAB2BGR)
    return cv2_to_pil(final_image)