https://asdfv1929.github.io/2018/05/11/saliency-LC/

或者以下代码实现

import numpy as np

import time

import cv2

def LC(image_gray):

image_height,image_width = image_gray.shape[:2]

base_matrix = np.zeros((256,256),dtype=np.int32)

base_line = np.array(range(256))

base_matrix[0] = base_line

for i in range(1,256):

base_matrix[i] = np.roll(base_line,i)

base_matrix = np.triu(base_matrix)

temp_matrix = np.triu(base_matrix).T

base_matrix = np.add(base_matrix ,temp_matrix)

hist_array = cv2.calcHist([image_gray], [0], None, [256], [0.0, 256.0])

hist_reshape = hist_array.reshape(1,256)

temp_matrix = np.tile(hist_reshape, (256, 1))

sum_diag_hist = np.sum(np.multiply(base_matrix,temp_matrix),axis=1)

image_gray_value = image_gray.reshape(1,image_height*image_width)[0]

image_gray_copy = np.zeros(image_height * image_width, dtype=np.int32)

for i,x in enumerate(image_gray_value):

image_gray_copy[i] = sum_diag_hist[x]

image_result = image_gray_copy.reshape(image_height,image_width)

image_result = (image_result-np.min(image_result))/(np.max(image_result)-np.min(image_result))

return image_result

if __name__ == '__main__':

file = r"C:\Users\xxx\Desktop\001.png"

start = time.time()

image_gray = cv2.imread(file, 0)

saliency_image = LC(image_gray)

# cv2.imwrite(r"C:\Users\xxx\Desktop\001_1.png",saliency_image*255)

end = time.time()

print("Duration: %.2f seconds." % (end - start))

cv2.imshow("gray saliency image", saliency_image)

cv2.waitKey(0)

cv2.destroyAllWindows()