在python中计算ssim的方法(与Matlab结果一致)-创新互联
如下代码可以计算输入的两张图像的结构相似度(SSIM),结果与matlab计算结果一致
创新互联主要从事成都网站制作、网站设计、外贸网站建设、网页设计、企业做网站、公司建网站等业务。立足成都服务武宣,十多年网站建设经验,价格优惠、服务专业,欢迎来电咨询建站服务:13518219792// An highlighted block import cv2 import numpy as np def ssim(img1, img2): C1 = (0.01 * 255)**2 C2 = (0.03 * 255)**2 img1 = img1.astype(np.float64) img2 = img2.astype(np.float64) kernel = cv2.getGaussianKernel(11, 1.5) window = np.outer(kernel, kernel.transpose()) mu1 = cv2.filter2D(img1, -1, window)[5:-5, 5:-5] # valid mu2 = cv2.filter2D(img2, -1, window)[5:-5, 5:-5] mu1_sq = mu1**2 mu2_sq = mu2**2 mu1_mu2 = mu1 * mu2 sigma1_sq = cv2.filter2D(img1**2, -1, window)[5:-5, 5:-5] - mu1_sq sigma2_sq = cv2.filter2D(img2**2, -1, window)[5:-5, 5:-5] - mu2_sq sigma12 = cv2.filter2D(img1 * img2, -1, window)[5:-5, 5:-5] - mu1_mu2 ssim_map = ((2 * mu1_mu2 + C1) * (2 * sigma12 + C2)) / ((mu1_sq + mu2_sq + C1) * (sigma1_sq + sigma2_sq + C2)) return ssim_map.mean() def calculate_ssim(img1, img2): '''calculate SSIM the same outputs as MATLAB's img1, img2: [0, 255] ''' if not img1.shape == img2.shape: raise ValueError('Input images must have the same dimensions.') if img1.ndim == 2: return ssim(img1, img2) elif img1.ndim == 3: if img1.shape[2] == 3: ssims = [] for i in range(3): ssims.append(ssim(img1, img2)) return np.array(ssims).mean() elif img1.shape[2] == 1: return ssim(np.squeeze(img1), np.squeeze(img2)) else: raise ValueError('Wrong input image dimensions.') img1 = cv2.imread("Test2_HR.bmp", 0) img2 = cv2.imread("Test2_LR2.bmp", 0) ss = calculate_ssim(img1, img2) print(ss)
当前题目:在python中计算ssim的方法(与Matlab结果一致)-创新互联
网页地址:http://myzitong.com/article/jhhic.html