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

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()