实验验证离散余弦变换和简单压缩应用，显示对应的原图，dct图和恢复的图像

离散余弦变换压缩

离散余弦变换

import cv2 import numpy as np import matplotlib.pyplot as plt img=cv2.imread("lena.jpg",0) img1=img.astype(np.float) img_dct=cv2.dct(img1) img_dct_log=np.log(abs(img_dct)) img_idct=cv2.idct(img_dct) plt.subplot(141) plt.imshow(img,cmap='gray') plt.title('original') plt.axis('off') plt.subplot(142) plt.imshow(img_dct_log,cmap='gray') plt.title('dct') plt.axis('off') plt.subplot(143) plt.imshow(img_idct,cmap='gray') plt.title('idct') plt.axis('off') plt.show()

压缩

import cv2 import numpy as np import matplotlib.pyplot as plt img=cv2.imread("lena.jpg",0) img1=img.astype(np.float32) img_dct=cv2.dct(img1) (rows,cols)=img_dct.shape for i in range(0,rows): for j in range(0,cols): if i>60 or j>60: img_dct[i,j]=0 img_dct_log=np.log(abs(img_dct)) img_dct=cv2.idct(img_dct) plt.subplot(141) plt.imshow(img,cmap='gray') plt.title('original') plt.axis('off') plt.subplot(142) plt.imshow(img_dct_log,cmap='gray') plt.title('dct') plt.axis('off') plt.subplot(143) plt.imshow(img_dct,cmap='gray') plt.title('idct') plt.axis('off') plt.show()