python SVD压缩图像的实现代码

# -*- coding: utf-8 -*-
'''
author@cclplus
date:2019/11/3
'''
import cv2
import matplotlib as mpl
import numpy as np
import matplotlib.pyplot as plt
#转为u8类型
def restore1(u, sigma, v, k):
  m = len(u)
  n = len(v)
  a = np.zeros((m, n))
  a = np.dot(u[:, :k], np.diag(sigma[:k])).dot(v[:k, :])
  a[a < 0] = 0
  a[a > 255] = 255
  return np.rint(a).astype('uint8')
def SVD(frame,K=10):
  a = np.array(frame)
  #由于是彩色图像，所以3通道。a的最内层数组为三个数，分别表示RGB，用来表示一个像素
  u_r, sigma_r, v_r = np.linalg.svd(a[:, :, 0])
  u_g, sigma_g, v_g = np.linalg.svd(a[:, :, 1])
  u_b, sigma_b, v_b = np.linalg.svd(a[:, :, 2])
  R = restore1(u_r, sigma_r, v_r, K)
  G = restore1(u_g, sigma_g, v_g, K)
  B = restore1(u_b, sigma_b, v_b, K)
  I = np.stack((R, G, B), axis = 2)
  return I
   

if __name__ == "__main__":
  mpl.rcParams['font.sans-serif'] = [u'simHei']
  mpl.rcParams['axes.unicode_minus'] = False
  frame = cv2.imread("./liuyifei.bmp")
  I = SVD(frame,40)
  plt.imshow(I)
  cv2.imwrite("out.bmp",I)