python实现JPEG算法压缩解压文件

根据提供的引用内容，JPEG算法是一种有损压缩算法，而且实现起来比较复杂。Python中有一些第三方库可以实现JPEG压缩和解压缩，比如Pillow和OpenCV。下面是使用Pillow库实现JPEG压缩和解压缩的示例代码：

压缩文件：

from PIL import Image

# 打开原始图像
img = Image.open('original.jpg')

# 将图像转换为YCbCr颜色空间
img_ycbcr = img.convert('YCbCr')

# 对每个颜色通道进行离散余弦变换（DCT）
img_dct = img_ycbcr.copy()
img_dct = img_dct.transform((img.width // 8, img.height // 8), Image.EXTENT, (8, 8), Image.DCT)

# 量化DCT系数
quantization_table = [
    [16, 11, 10, 16, 24, 40, 51, 61],
    [12, 12, 14, 19, 26, 58, 60, 55],
    [14, 13, 16, 24, 40, 57, 69, 56],
    [14, 17, 22, 29, 51, 87, 80, 62],
    [18, 22, 37, 56, 68, 109, 103, 77],
    [24, 35, 55, 64, 81, 104, 113, 92],
    [49, 64, 78, 87, 103, 121, 120, 101],
    [72, 92, 95, 98, 112, 100, 103, 99]
]
img_quantized = img_dct.copy()
for x in range(img_dct.width):
    for y in range(img_dct.height):
        img_quantized.putpixel((x, y), tuple([round(img_dct.getpixel((x, y))[i] / quantization_table[y % 8][x % 8]) for i in range(3)]))

# 将量化后的DCT系数写入文件
with open('compressed.jpg', 'wb') as f:
    for y in range(img_quantized.height):
        for x in range(img_quantized.width):
            for i in range(3):
                f.write(bytes([img_quantized.getpixel((x, y))[i]]))

解压文件：

from PIL import Image

# 从文件中读取量化后的DCT系数
with open('compressed.jpg', 'rb') as f:
    img_quantized = Image.new('YCbCr', (512, 512))
    for y in range(img_quantized.height):
        for x in range(img_quantized.width):
            img_quantized.putpixel((x, y), tuple([int.from_bytes(f.read(1), byteorder='big') for i in range(3)]))

# 反量化DCT系数
quantization_table = [
    [16, 11, 10, 16, 24, 40, 51, 61],
    [12, 12, 14, 19, 26, 58, 60, 55],
    [14, 13, 16, 24, 40, 57, 69, 56],
    [14, 17, 22, 29, 51, 87, 80, 62],
    [18, 22, 37, 56, 68, 109, 103, 77],
    [24, 35, 55, 64, 81, 104, 113, 92],
    [49, 64, 78, 87, 103, 121, 120, 101],
    [72, 92, 95, 98, 112, 100, 103, 99]
]
img_dct = img_quantized.copy()
for x in range(img_quantized.width):
    for y in range(img_quantized.height):
        img_dct.putpixel((x, y), tuple([img_quantized.getpixel((x, y))[i] * quantization_table[y % 8][x % 8] for i in range(3)]))

# 对每个颜色通道进行反离散余弦变换（IDCT）
img_ycbcr = img_dct.copy()
img_ycbcr = img_ycbcr.transform((img_dct.width * 8, img_dct.height * 8), Image.EXTENT, (8, 8), Image.IDCT)

# 将图像转换回RGB颜色空间
img_rgb = img_ycbcr.convert('RGB')

# 保存解压后的图像
img_rgb.save('uncompressed.jpg')