【图像隐写】基于高斯模型的JPEG图像隐写matlab源码
2021/7/9 12:36:53
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一、简介
二、源代码
% This example demonstrates how to use the MG embedding function clc clear all close all % Read the input cover image Cover = double(imread ('1.pgm')); % Set the payload to 0.4 bpp Payload = 0.4; % MG embedding tStart = tic; [Stego, pChange, ChangeRate] = MG( Cover, Payload ); tEnd = toc(tStart); fprintf('MG embedding is done in: %f (sec)\n',tEnd); %% figure; imshow (Cover,[]); title ('Cover image'); function [Stego, pChange, ChangeRate] = MG ( Cover, Payload ) % ------------------------------------------------------------------------- % Multivariate Gaussian Embedding | September 2015 | version 1.0 % ------------------------------------------------------------------------- % INPUT: % - Cover - Path to the cover image or the cover image itself. % - Payload - Embedding payload in bits per pixel (bpp). % OUTPUT: % - Stego - Resulting image with embedded payload % - pChange - Embedding change probabilities. % - ChangeRate - Average number of changed pixels % ------------------------------------------------------------------------- % Copyright (c) 2015 DDE Lab, Binghamton University, NY. % All Rights Reserved. % ------------------------------------------------------------------------- % Permission to use, copy, modify, and distribute this software for % educational, research and non-profit purposes, without fee, and without a % written agreement is hereby granted, provided that this copyright notice % appears in all copies. The program is supplied "as is," without any % accompanying services from DDE Lab. DDE Lab does not warrant the % operation of the program will be uninterrupted or error-free. The % end-user understands that the program was developed for research purposes % and is advised not to rely exclusively on the program for any reason. In % no event shall Binghamton University or DDE Lab be liable to any party % for direct, indirect, special, incidental, or consequential damages, % including lost profits, arising out of the use of this software. DDE Lab % disclaims any warranties, and has no obligations to provide maintenance, % support, updates, enhancements or modifications. % ------------------------------------------------------------------------- % Contact: vsedigh1@binghamton.edu | fridrich@binghamton.edu % September 2015 % http://dde.binghamton.edu/download/ % ------------------------------------------------------------------------- % References: % [1] - J. Fridrich and J. Kodovsky. Multivariate Gaussian model for % designing additive distortion for steganography. Proc. IEEE, ICASSP, % Vancouver, Canada, May 26-31, 2013. % ------------------------------------------------------------------------- % Read and convert the input cover image into double format if ischar( Cover ) Cover = double( imread(Cover) ); else Cover = double( Cover ); end % Compute Variance and do the flooring for numerical stability Variance = VarianceEstimation(Cover); Variance(Variance< 1) = 1; % Compute Fisher information and smooth it FisherInformation = 1./Variance.^2; % Compute embedding change probabilities and execute embedding FI = FisherInformation(:)'; % Ternary embedding change probabilities beta = TernaryProbs(FI,Payload); % Simulate embedding Stego = Cover; beta = 2 * beta; r = rand(1,numel(Cover)); ModifPM1 = (r < beta); % Cover elements to be modified by +-1 r = rand(1,numel(Cover)); Stego(ModifPM1) = Cover(ModifPM1) + 2*(round(r(ModifPM1))) - 1; % Modifying X by +-1 Stego(Stego>255) = 253; % Taking care of boundary cases Stego(Stego<0) = 2; ChangeRate = sum(ModifPM1(:))/numel(Cover); % Computing the change rate pChange = reshape(beta/2,size(Cover)); end
三、运行结果
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