【图像编码】基于二叉树和最优截断实现图像压缩算法附matlab代码

1 内容介绍

遥感影像数据量大，需要通过低复杂度算法进行压缩星载设备。具有自适应扫描顺序的二叉树编码（BTCA）是一种有效的算法为使命。但是，对于大尺度的遥感影像，BTCA 需要大量的内存，并且确实不提供随机访问属性。在本文中，我们提出了一种基于 BTCA 和优化截断。小波图像首先被分成几个单独编码的块由 BTCA 提供。根据 BTCA 的性质，我们仔细选择每个区块的有效截断点优化rate-distortion比率，使压缩比更高，内存要求更低并获得随机访问属性。没有任何熵编码，所提出的方法很简单而且速度快，非常适合星载设备。实验在三个遥控器上进行传感图像集，结果表明它可以显着提高 PSNR、SSIM 和 VIF，以及主观视觉体验。

2 仿真代码

%% matlab code for BTOT(Binary Tree and Optimized Truncation)% unoptimized, without head information, without entropy coding.% % Reference:% % Ke-Kun Huang, Hui Liu, Chuan-Xian Ren, Yu-Feng Yu and Zhao-Rong Lai. % Remote sensing image compression based on binary tree and optimized truncation.  % Digital Signal Processing, vol. 64, pp. 96-106, 2017.% http://dx.doi.org/10.1016/j.dsp.2017.02.008% % Email: kkcocoon@163.com% Homepage: http://www.scholat.com/huangkekun​clc;clear;close all%% -----------   Input   ----------------imname = 'SanDiego.bmp';I_Orig = double(imread(imname));​[row, col] = size(I_Orig);blksize = 64;  ​%% -----------   Wavelet Decomposition   -------------n_log = log2(row); level = floor(n_log);I_Dec = wavecdf97(I_Orig, level);    n_min = 1;brates = [0.0625, 0.125, 0.25, 0.5, 1];​%% -----------   Coding   ----------------[out_code, blklen, n_max, n_min, out_S,out_R,out_N] = encode(I_Dec, blksize, n_min);    ​%% -----------   Decoding   ----------------disp([ 'aa_BTOT_' imname(1:end-4) '=[']);for rate=brates    I_DecR = decode(out_code, blklen, n_max, n_min, blksize, row, rate, out_S,out_R,out_N);        I_Rec = wavecdf97(I_DecR, -level);    MSE = sum(sum((I_Rec - I_Orig).^2))/(row*row);    PSNR = 10*log10(255*255/MSE);    disp([sprintf('%.4f',rate) ' ' sprintf('%.2f',PSNR)]);   enddisp('];');figuresubplot(121)imshow(I_Orig,[]);title('原图')subplot(122)imshow(I_Rec,[]);title('压缩图')

3 运行结果

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