直方图应用

其他

发布时间 : 2021-01-02 15:21

阅读 :

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt


def equalHist_demo(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    dst = cv.equalizeHist(gray)
    cv.imshow('equalHist_demo', dst)

def clahe_demo(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    clahe = cv.createCLAHE(clipLimit=5.0, tileGridSize=(8, 8))
    dst = clahe.apply(gray)
    cv.imshow('clahe_demo', dst)

def create_rgb_hist(image):
    h,w, c = image.shape
    rgbHist = np.zeros([16*16*16, 1], np.float32)
    bsize = 256 / 16
    for row in range(h):
        for col in range(w):
            b = image[row, col, 0]
            g = image[row, col, 1]
            r = image[row, col, 2]
            index = (b/ bsize)*16*16 + np.int(g/bsize)*16 + np.int(r/bsize)
            rgbHist[np.int(index), 0] += 1
        return rgbHist

def hist_compare(image1, image2):
    hist1 = create_rgb_hist(image1)
    hist2 = create_rgb_hist(image2)
    match1 = cv.compareHist(hist1,hist2, cv.HISTCMP_BHATTACHARYYA)
    match2 = cv.compareHist(hist1, hist2, cv.HISTCMP_CORREL)
    match3 = cv.compareHist(hist1, hist2, cv.HISTCMP_CHISQR)
    print('巴氏距离:{}, 相关性:{}, 卡方:{}'.format(match1, match2, match3))


src = cv.imread('./5.jpg')  # blue, green, red
cv.namedWindow('input image', cv.WINDOW_AUTOSIZE)
# cv.imshow('input image', src)
# equalHist_demo(src)

image1 = cv.imread('1.jpg')
image2 = cv.imread('2.jpg')
cv.imshow('image1', image1)
cv.imshow('image2', image2)
hist_compare(image1, image2)
clahe_demo(src)
cv.waitKey(0)

cv.destroyAllWindows()

转载请注明来源，欢迎对文章中的引用来源进行考证，欢迎指出任何有错误或不够清晰的表达。可以在下面评论区评论，也可以邮件至 2621041184@qq.com