拉普拉斯金字塔工具箱

% LPDEMO % Demo of the Laplacian pyramid functions x = imread('cameraman.tif'); x = double(x)/256; % Laplacian decomposition using 9/7 filters and 5 levels pfilt = '9/7'; n = 5; y = lpd(x, '9/7', n); % Display output figure(1) colormap(gray) nr = floor(sqrt(n+1)); nc = ceil((n+1)/nr); for l = 1:n+1 subplot(nr, nc, l); imageshow(y{l}); end % Reconstruction xr = lpr(y, pfilt); % Show perfect reconstruction figure(2) colormap(gray) subplot(1,2,1), imageshow(x, [0, 1]); subplot(1,2,2), imageshow(xr, [0, 1]); title(sprintf('SNR = %.2f dB', SNR(x, xr))) % Reconstruction with only R percent of most significant coefficients r = input('Enter the percentage of retained coefficients (say 10): '); if isempty(r) r = 10; end if ~isnumeric(r) | (r < 0) | (r > 100) error('Please enter a number between 0 and 100'); end % Put all coefficients in one column vector for processing [c, s] = lp2vec(y); % Sort the coefficient in the order of magnitude csort = sort(abs(c)); csort = flipud(csort); % Threshold to retain only R percent of most significant coefficients nc = sum(prod(s, 2)); m = round(nc/100*r); thresh = csort(m); cr = c .* (abs(c) >= thresh); % Reconstruction y = vec2lp(cr, s); xr = lpr(y, pfilt); figure(2) colormap(gray) subplot(1,2,1), imageshow(x, [0, 1]); subplot(1,2,2), imageshow(xr, [0, 1]); title(sprintf('Reconstruction with %.1f%% of coefs\nSNR = %.2f dB', ... r, SNR(x, xr))); % Now compare with the old reconstruction method input('Press Enter key to continue...'); xr1 = lpr_old(y, pfilt); subplot(1,2,1), imageshow(xr1, [0, 1]); title(sprintf('Reconstruction using the old method\nSNR = %.2f dB', ... SNR(x, xr1)));