【发布时间】:2021-01-30 09:11:29
【问题描述】:
我的想法是先使用dwt2 分解图像,然后将dct2 应用于coefficients_approximation,将水印应用于结果,然后重新组合图像。
final_image = idwt2( idct2 ( dct2 ( dwt2 (starting_image))))
但是每当我这样做时,我都会失去很多质量,我不知道为什么。这是代码,你知道吗?
clear all; clc;
% read lena img
lena = double(imread('lena.jpg'));
% read watermark img
%w = imread('mark.png');
load cookiebears.mat
% compure DWT on lena and watermark
[approximate_lena, horizontal_lena, vertical_lena, diagonal_lena] = dwt2(lena, 'haar');
% i have to save the image first and then open it in order to use it in
% dct2() omitting this step generate an error
imwrite(uint8(approximate_lena), 'ca_lena.jpg');
% read approximate_lena layer in a variable
lena_ca = double(imread('ca_lena.jpg'));
% perform DCT on approximation level of lena picture
dct_lena = dct2(lena_ca);
% embed the watermark into dct_lena
% insert here function to embed the watermark
% dct_lena = insert_watermark();
% now I can recompose the lena coefficients approximation
lena_ca_recomposed = idct2(dct_lena);
% recompose DWT
lena_recomposed = idwt2(lena_ca_recomposed, horizontal_lena,vertical_lena, diagonal_lena, 'haar');
如下所示:
在第一行中,左侧是起始图片,右侧是最终图片(更暗,细节更少)。
在左侧的第二行中,我们比较了原始图像上 dwt2 之后的 CA 和右侧用 idct2 重组的 CA
【问题讨论】:
标签: matlab image-processing dct dwt