帮我写一个malab的基于离散余弦变换的图片压缩代码
时间: 2024-06-04 18:12:31 浏览: 10
以下是基于离散余弦变换的图片压缩代码:
%% 图片压缩
% 读取图片文件
img = imread('lena.jpg');
img = rgb2gray(img);
% 定义块大小和步长
blockSize = 8;
stepSize = 8;
% 获取图片尺寸
[M, N] = size(img);
% 将图片分块
blocks = zeros(blockSize, blockSize, M/blockSize*N/blockSize);
for i = 1 : M/blockSize
for j = 1 : N/blockSize
block = img((i-1)*blockSize+1 : i*blockSize, (j-1)*blockSize+1 : j*blockSize);
blocks(:, :, (i-1)*N/blockSize+j) = block;
end
end
% 对每个块进行离散余弦变换
dctBlocks = zeros(blockSize, blockSize, M/blockSize*N/blockSize);
for i = 1 : M/blockSize*N/blockSize
block = blocks(:, :, i);
dctBlock = dct2(block);
dctBlocks(:, :, i) = dctBlock;
end
% 对每个块进行量化
quantizedBlocks = zeros(blockSize, blockSize, M/blockSize*N/blockSize);
Q = [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];
for i = 1 : M/blockSize*N/blockSize
dctBlock = dctBlocks(:, :, i);
quantizedBlock = round(dctBlock ./ (Q * 0.1));
quantizedBlocks(:, :, i) = quantizedBlock;
end
% 对每个块进行反量化
dequantizedBlocks = zeros(blockSize, blockSize, M/blockSize*N/blockSize);
for i = 1 : M/blockSize*N/blockSize
quantizedBlock = quantizedBlocks(:, :, i);
dequantizedBlock = quantizedBlock .* (Q * 0.1);
dequantizedBlocks(:, :, i) = dequantizedBlock;
end
% 对每个块进行反离散余弦变换
idctBlocks = zeros(blockSize, blockSize, M/blockSize*N/blockSize);
for i = 1 : M/blockSize*N/blockSize
dequantizedBlock = dequantizedBlocks(:, :, i);
idctBlock = idct2(dequantizedBlock);
idctBlocks(:, :, i) = idctBlock;
end
% 重构图片
reconstructedImg = zeros(M, N);
for i = 1 : M/blockSize
for j = 1 : N/blockSize
block = idctBlocks(:, :, (i-1)*N/blockSize+j);
reconstructedImg((i-1)*blockSize+1 : i*blockSize, (j-1)*blockSize+1 : j*blockSize) = block;
end
end
% 显示原图片和重构图片
subplot(1, 2, 1);
imshow(img);
title('原图片');
subplot(1, 2, 2);
imshow(uint8(reconstructedImg));
title('重构图片');