matlab实现JPEG图像压缩的代码
时间: 2023-10-12 16:04:38 浏览: 72
以下是一个简单的 MATLAB 代码实现 JPEG 图像压缩:
```matlab
% 读入图像
img = imread('image.jpg');
% 将图像转换为灰度图像
gray_img = rgb2gray(img);
% 块大小
block_size = 8;
% 将图像分成块
blocks = mat2cell(gray_img, block_size * ones(1, size(gray_img, 1) / block_size), block_size * ones(1, size(gray_img, 2) / block_size));
% 量化表
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];
% 块的数量
num_blocks = numel(blocks);
% 压缩后的数据
compressed_data = zeros(1, block_size^2 * num_blocks);
% 对每个块进行离散余弦变换和量化
for i = 1:num_blocks
block = blocks{i};
dct_block = dct2(block - 128);
quantized_block = round(dct_block ./ (quantization_table * quality_factor));
compressed_data((i - 1) * block_size^2 + 1:i * block_size^2) = quantized_block(:)';
end
% 保存压缩后的数据
save('compressed_data.mat', 'compressed_data');
% 解压缩
% 读入压缩后的数据
load('compressed_data.mat');
% 解压缩后的图像
uncompressed_img = zeros(size(gray_img));
% 对每个块进行逆量化和逆离散余弦变换
for i = 1:num_blocks
compressed_block = compressed_data((i - 1) * block_size^2 + 1:i * block_size^2);
quantized_block = reshape(compressed_block, [block_size, block_size]);
dct_block = quantized_block .* (quantization_table * quality_factor);
block = idct2(dct_block) + 128;
uncompressed_img((i - 1) * block_size + 1:i * block_size, (i - 1) * block_size + 1:i * block_size) = block;
end
% 显示解压缩后的图像
imshow(uncompressed_img, []);
```
其中,`quality_factor` 是一个可以调整压缩质量的参数,值越大压缩质量越低,压缩率越高。