sir, what is required to denoise the attached image, i tried with following code but still some noise is there

clc; close all; %% %roiFolder = 'E:\MATLAB\R2016b\bin\img\PCA\my_PhD_Programs\Jermanfilter\dbROI'; %filePattern = fullfile(myFolder, '*.bmp'); %dataFiles = dir(filePattern);

myFolder = 'E:\MATLAB\R2016b\bin\img\PCA\my_PhD_Programs\Jermanfilter\db\Test'; for iuser=1:1 path1=strcat('E:\MATLAB\R2016b\bin\img\PCA\my_PhD_Programs\Jermanfilter\dbROI\',num2str(iuser)); mkdir(path1); path1=strcat(path1,'\'); for irep=1:1 fname=num2str(irep); nnfile=[myFolder,'\',num2str(iuser,'%d')]; nfile=[nnfile,'\',num2str(irep,'%d'),'.bmp']; % nfile=[nnfile,'mano-',num2str(iuser,'%3.3d'),'-',num2str(irep,'%3.3d'),'.bmp']; % a=imread(nfile,'bmp');

       I=imread(nfile,'bmp');

% preprocess the input a little bit Ip = single(I); thr = prctile(Ip(Ip(:)>0),1) * 0.9; Ip(Ip<=thr) = thr; Ip = Ip - min(Ip(:)); Ip = Ip ./ max(Ip(:));

% compute enhancement for two different tau values %V1 = vesselness2D(Ip, 0.5:0.5:2.5, [1;1], 1, false); I = vesselness2D(Ip, 0.5:0.5:2.5, [1;1], 0.5, false);

%% Thresholding bw = adaptivethresh(I,45,1,'median','relative'); % Wellner's adaptive thresholding 50 2 %bw=adaptivethreshold(y,40,0.02,1); % adaptive thresholding % subplot(2,3,3); % imshow(bw); % title('Wellners adaptive thresholding');

%%low pass filter
G = fspecial('gaussian',[5 5],1);                                    %0.8
bw = imfilter(bw,G,'full');
% figure,
% imshow(bw);

 img1 =noisecomp(bw,3,7,3,6,1);
% figure,
% imshow(img1);

kernel = [-1, -1, -1; -1,8, -1; -1, -1, -1]; % 3 by 3 window.

bw = imfilter(img1, kernel); figure, imshow(bw);

%% saving images

bw = imresize(bw,[110 110]); imwrite(bw,[path1,num2str(irep),'.bmp']); % writing images in

end

% hold on; % plot(j,i,'rx'); end