图像处理压缩的matlab代码2

以下是一个基于JPEG标准的图像压缩的MATLAB代码示例：

% 读入图像
img = imread('lena.png');

% 将图像转为灰度图
grayImg = rgb2gray(img);

% 分块大小
blockSize = 8;

% 获取图像的大小
[height, width] = size(grayImg);

% 将图像按照分块大小进行分块
blocks = mat2cell(grayImg, blockSize * ones(1, height/blockSize), blockSize * ones(1, width/blockSize));

% 初始化量化矩阵
quantMatrix = [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];

% 初始化直流系数矩阵和交流系数矩阵
dcCoeffs = [];
acCoeffs = [];

% 对每个分块进行离散余弦变换和量化
for i = 1:numel(blocks)
    block = blocks{i};
    
    % 将块中的值减去128，使得变换后的值域在[-128, 127]
    block = block - 128;
    
    % 进行离散余弦变换
    dctBlock = dct2(block);
    
    % 量化
    quantizedBlock = round(dctBlock ./ (quantMatrix));
    
    % 将直流系数和交流系数分别提取出来
    dcCoeffs = [dcCoeffs quantizedBlock(1)];
    acCoeffs = [acCoeffs quantizedBlock(2:end)];
    
    % 将量化后的块写入新的矩阵中
    quantizedBlocks{i} = quantizedBlock;
end

% 将直流系数进行差分编码
diffDCCoeffs = diff(dcCoeffs);

% 对差分编码后的直流系数进行霍夫曼编码
huffmanDCCodes = huffmanenco(diffDCCoeffs, huffmandict(diffDCCoeffs));

% 对交流系数进行霍夫曼编码
acCoeffs = acCoeffs(:);
huffmanACCodes = huffmanenco(acCoeffs, huffmandict(acCoeffs));

% 将直流系数和交流系数的编码合并
huffmanCodes = [huffmanDCCodes; huffmanACCodes];

% 将编码写入文件
fid = fopen('compressed.bin', 'w');
fwrite(fid, huffmanCodes, 'ubit1');
fclose(fid);

这个代码实现了JPEG标准的图像压缩过程，包括离散余弦变换、量化、差分编码、霍夫曼编码等步骤。注意，这个代码只实现了压缩过程，解压缩过程需要另外的代码实现。