0001 0002 function IMM=mi_kernel_denoising(Im2,epsilon,Csvm,sigma,perfil_eps) 0003 0004 0005 load C_profile 0006 perfil_sigma=[1 1 1 1]; 0007 0008 sigma_2 = sigma; 0009 sigma_1 = sigma_2/2; 0010 AAlfa=linspace(-90,90,9); 0011 0012 for n=1:8 0013 Kernel_M(:,:,n) = kernelgauss2Dsteerable(16,sigma_2,sigma_1,AAlfa(n)); 0014 end 0015 0016 perfil_eps_M = perfil_eps*epsilon; 0017 perfil_C_M = perfil_C*Csvm; 0018 0019 ESCALAS=4; 0020 ORIENTACIONES=7; 0021 [pyrR,ind]=buildSFpyr(Im2,ESCALAS,ORIENTACIONES); 0022 0023 L=(1:256)'; 0024 UNOS=ones(1,256)'; 0025 pyr2=pyrR; 0026 for esc=1:ESCALAS 0027 for or=1:ORIENTACIONES+1 0028 fprintf('.') 0029 BAND_NUM=1+or+(esc-1)*(ORIENTACIONES+1); 0030 INDD=pyrBandIndices(ind,BAND_NUM); 0031 0032 RES = pyrBand(pyrR, ind, BAND_NUM); 0033 KB=Kernel_M(:,:,or).^(perfil_sigma(esc)); 0034 0035 P_C = perfil_C_M(INDD(1)); 0036 P_E = perfil_eps_M(INDD(1)); 0037 0038 R=blkproc(RES,[16 16],'SVRegression(x,P1,P2,P3,P4,P5)',L,KB,P_C,P_E,UNOS); 0039 0040 pyr2(INDD)=R(:); 0041 0042 end 0043 end 0044 pyr2(1:256*256)=zeros; 0045 IMM=reconSFpyr(pyr2,ind); 0046 0047 fprintf('\n')