JPEG压缩算法 MATLAB

function jpeg

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%
%%      THIS WORK IS SUBMITTED BY:
%%
%%      OHAD GAL
%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
close all;

% ==================
% section 1.2 + 1.3
% ==================
% the following use of the function:    
%
%    plot_bases（ base_sizeresolutionplot_type ）
%
% will plot the 64 wanted bases. I will use “zero-padding“ for increased resolution
% NOTE THAT THESE ARE THE SAME baseS !
% for reference I plot the following 3 graphs:
% a） 3D plot with basic resolution （64 plots of 8x8 pixels） using “surf“ function
% b） 3D plot with x20 resolution （64 plots of 160x160 pixels） using “mesh“ function
% c） 2D plot with x10 resolution （64 plots of 80x80 pixels） using “mesh“ function
% d） 2D plot with x10 resolution （64 plots of 80x80 pixels） using “imshow“ function
%
% NOTE: matrix size of pictures （b）（c） and （d） can support higher frequency = higher bases
%       but I am not asked to draw these （higher bases） in this section !
%       the zero padding is used ONLY for resolution increase !
%
% get all base pictures （3D surface figure）
plot_bases（ 81‘surf3d‘ ）;

% get all base pictures （3D surface figure） x20 resolution
plot_bases（ 820‘mesh3d‘ ）;

% get all base pictures （2D mesh figure） x10 resolution
plot_bases（ 810‘mesh2d‘ ）;   

% get all base pictures （2D mesh figure） x10 resolution
plot_bases（ 810‘gray2d‘ ）;   



% ==================
% section 1.4 + 1.5
% ==================
% for each picture {‘0‘..‘9‘} perform a 2 dimensional dct on 8x8 blocks.
% save the dct inside a cell of the size: 10 cells of 128x128 matrix
% show for each picture it‘s dct 8x8 block transform.

for idx = 0:9
   
   % load a picture
   switch idx
   case {01} input_image_128x128 = im2double（ imread（ sprintf（ ‘%d.tif‘idx ）‘tiff‘ ） ）;
   otherwise input_image_128x128 = im2double（ imread（ sprintf（ ‘%d.tif‘idx）‘jpeg‘ ） ）;
   end   
   
   % perform DCT in 2 dimension over blocks of 8x8 in the given picture
   dct_8x8_image_of_128x128{idx+1} = image_8x8_block_dct（ input_image_128x128 ）;

   if （mod（idx2）==0）
      figure;
   end     
   subplot（22mod（idx2）*2+1）;            
   imshow（input_image_128x128）;
   title（ sprintf（‘image #%d‘idx） ）;
   subplot（22mod（idx2）*2+2）;             
   imshow（dct_8x8_image_of_128x128{idx+1}）;
   title（ sprintf（‘8x8 DCT of image #%d‘idx） ）;
end



% ==================
% section 1.6
% ==================
% do statistics on the cell array of the dct transforms
% create a matrix of 8x8 that will describe the value of each “dct-base“ 
% over the transform of