comparison examples/Image Denoising/SMALL_ImgDenoise_DL_test_Training_size.m @ 19:79e1d62f0115

(none)

     Edata=sqrt(prod(SMALL.Problem.blocksize)) * SMALL.Problem.sigma * SMALL.Problem.gain;
     SMALL.DL(1).param=struct(...
         'Edata', Edata,...
         'initdict', SMALL.Problem.initdict,...
         'dictsize', SMALL.Problem.p,...
-        'iternum', 20,...
-        'memusage', 'high');
+        'iternum', 20);
+        %'memusage', 'high');
     
     %   Learn the dictionary
     
     SMALL.DL(1) = SMALL_learn(SMALL.Problem, SMALL.DL(1));
     

 figure('Name', 'KSVD vs SPAMS');
 
 subplot(1,2,1); plot(Training_size, time(1,:), 'ro-', Training_size, time(2,:), 'b*-');
 legend('KSVD','SPAMS',0);
 title('Time vs Training size');
+xlabel('Training Size (Num. of patches)');
+ylabel('Time(s)');
 subplot(1,2,2); plot(Training_size, psnr(1,:), 'ro-', Training_size, psnr(2,:), 'b*-');
 legend('KSVD','SPAMS',0);
 title('PSNR vs Training size');
+xlabel('Training Size (Num. of patches)');
+ylabel('PSNR(dB)');