在python3下对图像先转换为YCbCr格式的数据,再数据分块(8x8大小)使用OpenCV的离散余弦变换DCT的完整代码
时间: 2024-03-10 08:48:13 浏览: 16
以下是在Python3下对图像先转换为YCbCr格式的数据,再数据分块(8x8大小)使用OpenCV的离散余弦变换DCT的完整代码:
```python
import cv2
import numpy as np
# 读取图像
img_rgb = cv2.imread('test.jpg')
# 将图像转换为YCbCr格式的数据
img_ycc = cv2.cvtColor(img_rgb, cv2.COLOR_RGB2YCrCb)
# 对YCbCr格式的数据进行分块
blocks = img_ycc.reshape(-1, 8, 8, 3)
# 对每个块进行离散余弦变换(DCT)
dct_blocks = []
for block in blocks:
y, cb, cr = cv2.split(block)
y_dct = cv2.dct(np.float32(y)/255.0) # 对Y通道进行DCT
cb_dct = cv2.dct(np.float32(cb)/255.0) # 对Cb通道进行DCT
cr_dct = cv2.dct(np.float32(cr)/255.0) # 对Cr通道进行DCT
dct_block = cv2.merge([y_dct, cb_dct, cr_dct]) # 合并DCT后的通道
dct_blocks.append(dct_block)
dct_blocks = np.array(dct_blocks)
# 对DCT后的块进行处理,例如压缩、量化等
# 将处理后的块进行逆离散余弦变换(IDCT),得到处理后的YCbCr格式数据
idct_blocks = []
for dct_block in dct_blocks:
y_dct, cb_dct, cr_dct = cv2.split(dct_block)
y_idct = cv2.idct(y_dct) # 对Y通道进行IDCT
cb_idct = cv2.idct(cb_dct) # 对Cb通道进行IDCT
cr_idct = cv2.idct(cr_dct) # 对Cr通道进行IDCT
idct_block = cv2.merge([y_idct, cb_idct, cr_idct]) # 合并IDCT后的通道
idct_blocks.append(idct_block)
idct_blocks = np.array(idct_blocks)
# 将块合并成完整的图像
img_processed = idct_blocks.reshape(img_ycc.shape)
img_processed = cv2.cvtColor(img_processed, cv2.COLOR_YCrCb2RGB)
# 显示原始图像和处理后的图像
cv2.imshow('Original', img_rgb)
cv2.imshow('Processed', img_processed)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
需要注意的是,在进行DCT和IDCT时,需要将通道数据类型转换为float32,并将像素值归一化到0~1之间,以避免数据溢出。