% Matlab implementation of SPIHT (without Arithmatic coding stage)

%

% By Jing Tian, scuteejtian@hotmail.com

fprintf('-----------   Welcome to SPIHT Matlab Demo!   ----------------\n');



fprintf('-----------   Load Image   ----------------\n');

infilename = 'lena512.bmp';

outfilename = 'lena512_reconstruct.bmp';



Orig_I = double(imread(infilename));



rate = 1;



OrigSize = size(Orig_I, 1);

max_bits = floor(rate * OrigSize^2);

OutSize = OrigSize;

image_spiht = zeros(size(Orig_I));

[nRow, nColumn] = size(Orig_I);



fprintf('done!\n');

fprintf('-----------   Wavelet Decomposition   ----------------\n');

n = size(Orig_I,1);

n_log = log2(n);

level = n_log;

% wavelet decomposition level can be defined by users manually.

type = 'bior4.4';

[Lo_D,Hi_D,Lo_R,Hi_R] = wfilters(type);



[I_W, S] = func_DWT(Orig_I, level, Lo_D, Hi_D);



fprintf('done!\n');



fprintf('-----------   Encoding   ----------------\n');

img_enc = func_SPIHT_Enc(I_W, max_bits, nRow*nColumn, level);  



fprintf('done!\n');

fprintf('-----------   Decoding   ----------------\n');

img_dec = func_SPIHT_Dec(img_enc);



fprintf('done!\n');

fprintf('-----------   Wavelet Reconstruction   ----------------\n');

img_spiht = func_InvDWT(img_dec, S, Lo_R, Hi_R, level);



fprintf('done!\n');

fprintf('-----------   PSNR analysis   ----------------\n');



imwrite(img_spiht, gray(256), outfilename, 'bmp');



Q = 255;

MSE = sum(sum((img_spiht-Orig_I).^2))/nRow / nColumn;

fprintf('The psnr performance is %.2f dB\n', 10*log10(Q*Q/MSE));