【图像去噪】基于Matlab实现 SAR（合成孔径雷达）图像去噪.zip

function [thresh MSE PSNR EI] = bft(OI,A,B,C,level,n,type,thresh) % This function bft implements Brute Force Thresholding Algorithm as % specified in the paper entitled as Despeckling of SAR Image Using % Adaptive and Mean Filters, by Syed Musharaf Ali, Muhammad Younus Javed, % and Naveed Sarfraz Khattak % % INPUT: % OI = Original Image % A = Nondecimated 2-D wavelet transform of OI % B = Nondecimated 2-D wavelet transform of Filtered OI % C = Nondecimated 2-D wavelet transform of Filtered OI % level = Decomposition level % n = Number of spacing between minimum and maximum threshold % (Larger n results time consuming) % OUTPUT: % thresh = matrix of dimenshion (3*level,n)containing threshold % value % MSE = Mean Square Error % PSNR = Peak Singal to Noise Ratio % % % Implemented by ASHISH MESHRAM % meetashish85@gmail.com http://www.facebook.com/ashishmeet % Checking Input Arguments if nargout==4 && nargin<8 error('Not enough input arguments'); end if nargin<7||isempty(type) type = 'try'; end if nargin<6,error('Not enough input arguments');end if nargin<5,error('Not enough input arguments');end if nargin<4,error('Not enough input arguments');end if nargin<3,error('Not enough input arguments');end if nargin<2,error('Not enough input arguments');end if nargin<1,error('Not enough input arguments');end % Implementation Starts Here switch lower(type) case 'try' % Case for finding Best Threshold if level == 1 % First level decomposition ALH1 = A.dec{2,1};BLH1 = B.dec{2,1};CLH1 = C.dec{2,1}; % Vertical Detail AHL1 = A.dec{3,1};BHL1 = B.dec{3,1};CHL1 = C.dec{3,1}; % Horizonatal Detail AHH1 = A.dec{4,1};BHH1 = B.dec{4,1};CHH1 = C.dec{4,1}; % Diagonal Detail % Find minimum and maximum value of coefficients of each detail sub band Aminmax = [min(min(ALH1)) max(max(ALH1));... min(min(AHL1)) max(max(AHL1));... min(min(AHH1)) max(max(AHH1))]; % Preallocating thresh = zeros(3,n); MSE = zeros(3,n); PSNR = zeros(3,n); % Vertical Detail coeff = linspace(Aminmax(1,1),Aminmax(1,2),n); for k = 1:length(coeff) % Replacing Low Level pixel of Image A with Image B disp('Replacing Low Level pixel of Image A with Image B'); ALH1(ALH1<coeff(k)) = CLH1(ALH1<coeff(k)); % Applying Direction Dependent Mask disp('Applying Direction Dependent Mask'); ALH1 = ddm(ALH1,BLH1,coeff(k),'LH'); % Applying Direction Smoothing Filter disp('Applying Direction Smoothing Filter'); ALH1 = dsf(ALH1,3); % Replacing decomposition coefficients with new coefficients disp('Replacing decomposition coefficients with new coefficients'); A.dec{2,1} = ALH1; A.dec{3,1} = AHL1; A.dec{4,1} = AHH1; % Inverse nondecimated 2-D wavelet transform disp('Inverse nondecimated 2-D wavelet transform'); EI = indwt2(A,'aa',1); % Computing Results disp('Computing Results'); [MSE(1,k) PSNR(1,k)] = MetricsMeasurement(OI,EI); thresh(1,k) = coeff(k); end % Horizontal Detail coeff = linspace(Aminmax(2,1),Aminmax(2,2),n); for k = 1:length(coeff) % Replacing Low Level pixel of Image A with Image B disp('Replacing Low Level pixel of Image A with Image B'); AHL1(AHL1<coeff(k)) = CHL1(AHL1<coeff(k)); % Applying Direction Dependent Mask disp('Applying Direction Dependent Mask'); AHL1 = ddm(AHL1,BHL1,coeff(k),'HL'); % Applying Direction Smoothing Filter disp('Applying Direction Smoothing Filter'); AHL1 = dsf(AHL1,3); % Replacing decomposition coefficients with new coefficients disp('Replacing decomposition coefficients with new coefficients'); A.dec{2,1} = ALH1; A.dec{3,1} = AHL1; A.dec{4,1} = AHH1; % Inverse nondecimated 2-D wavelet transform disp('Inverse nondecimated 2-D wavelet transform'); EI = indwt2(A,'aa',1); % Computing Results disp('Computing Results'); [MSE(2,k) PSNR(2,k)] = MetricsMeasurement(OI,EI); thresh(2,k) = coeff(k); end % Diagonal Detail coeff = linspace(Aminmax(3,1),Aminmax(3,2),n); for k = 1:length(coeff) % Replacing Low Level pixel of Image A with Image B disp('Replacing Low Level pixel of Image A with Image B'); AHH1(AHH1<coeff(k)) = CHH1(AHH1<coeff(k)); % Applying Direction Dependent Mask disp('Applying Direction Dependent Mask'); AHH1 = ddm(AHH1,BHH1,coeff(k),'HH'); % Applying Direction Smoothing Filter disp('Applying Direction Smoothing Filter'); AHH1 = dsf(AHH1,3); % Replacing decomposition coefficients with new coefficients disp('Replacing decomposition coefficients with new coefficients'); A.dec{2,1} = ALH1; A.dec{3,1} = AHL1; A.dec{4,1} = AHH1; % Inverse nondecimated 2-D wavelet transform disp('Inverse nondecimated 2-D wavelet transform'); EI = indwt2(A,'aa',1); % Computing Results disp('Computing Results'); [MSE(3,k) PSNR(3,k)] = MetricsMeasurement(OI,EI); thresh(3,k) = coeff(k); end elseif level == 2 % Second level decomposition ALH2 = A.dec{2,1};BLH2 = B.dec{2,1};CLH2 = C.dec{2,1}; % Vertical Detail AHL2 = A.dec{3,1};BHL2 = B.dec{3,1};CHL2 = C.dec{3,1}; % Horizonatal Detail AHH2 = A.dec{4,1};BHH2 = B.dec{4,1};CHH2 = C.dec{4,1}; % Diagonal Detail ALH1 = A.dec{5,1};BLH1 = B.dec{5,1};CLH1 = C.dec{5,1}; % Vertical Detail AHL1 = A.dec{6,1};BHL1 = B.dec{6,1};CHL1 = C.dec{6,1}; % Horizonatal Detail AHH1 = A.dec{7,1};BHH1 = B.dec{7,1};CHH1 = C.dec{7,1}; % Diagonal Detail % Find minimum and maximum value of coefficients of each detail sub band Aminmax = [min(min(ALH2)) max(max(ALH2));... min(min(AHL2)) max(max(AHL2));... min(min(AHH2)) max(max(AHH2));... min(min(ALH1)) max(max(ALH1));... min(min(AHL1)) max(max(AHL1));... min(min(AHH1)) max(max(AHH1))]; % Preallocating thresh = zeros(6,n); MSE = zeros(6,n); PSNR = zeros(6,n); % Vertical Detail coeff = linspace(Aminmax(1,1),Aminmax(1,2),n); for k = 1:length(coeff) % Replacing Low Level pixel of Image A with Image B disp('Replacing Low Level pixel of Image A with Image B'); ALH2(ALH2<coeff(k)) = CLH2(ALH2<coeff(k)); % Applying Direction Dependent Mask disp('Applying Direction Dependent Mask'); ALH2 = ddm(ALH2,BLH2,coeff(k),'LH'); % Applying Direction Smoothing Filter disp('Applying Direction Smoothing Filter');