在python3下使用OpenCV做离散余弦变换DCT及其反变换IDCT

对图像处理经常用到DCT, Python下有很多带有DCT算法包, 这里使用OpenCV的DCT做变换, 并简单置0部分数据, 再查看反变换图像的效果.

import numpy as np

import cv2

# from matplotlib import pyplot as plt

y = cv2.imread('window.bmp', 0)

# print(y.shape)

cv2.imshow("gray",y)

y1 = y.astype(np.float32)

# print(y1.dtype)

Y = cv2.dct(y1)

print(Y.shape)

for i in range(0,240):
     for j in range(0,320):
         if i > 100 or j > 100:
             Y[i,j] = 0

cv2.imshow("Dct",Y)

y2 = cv2.idct(Y)

# print(y2.dtype)

cv2.imshow("iDCT",y2.astype(np.uint8))

cv2.waitKey(0)

对于320x240的图像, 在频域对大于100的行和列都置零(相当于低通滤波)后, 反变换后图像有点模糊, 但还能还原大致效果.

cnblogs Tags: python, opencv, DCT