We Helped With This Electrical Engineering Assignment: Have A Similar One?

function Iout = hw2filters(type,filename)
%function to apply selected filters to an image and animate
try
    I = imadjust(imread(filename));
catch
    error('--> cannot read file <--');
end

figure;
subplot 122

%make image double for subsequent filtering
I=double (I)
% imshow(I,[0 255]); % the range must be specificed for double images
%note: I'm displaying again becasue of a bug in Matlab ...
subplot 121
imshow(I, [0 255]);

switch lower(type)
    case {'thresh'}
        disp('Thresholding');
        Iout=thresh(I);
    case {'median'}
        disp('Median Filter');
        Iout=median(I,20);
    case {'blur_gauss'}
        disp('Blurring Gaussian');
        Iout=blur_gauss(I,20);
     case {'log'}
        disp('Blurring Laplacian of Gaussian');
        Iout=log(I,11,2);    
    case {'blur_laplace'}
        disp('Blurring Laplacian');
        Iout=blur_laplace(I,1);
    case {'blur_ave'}
        disp('Bluring Using Average ');
        Iout=blur_ave(I,11);
    case {'unsharp'}
        disp('Unsharpening');
        Iout=unsharp(I,3,2);
    case {'blur_disk'}
        disp('Blurring Disk Filter');
        Iout=blur_disk(I,10);    
    case {'hor_prewitt_edge'}
        disp('Prewitt Horizontal Edge');
        Iout=hor_prewitt_edge(I);
    case {'ver_prewitt_edge'}
        disp('Prewitt Vertical Edge');
        Iout=ver_prewitt_edge(I);
    case {'hor_sobel_edge'}
        disp('Sobel Horizontal Edge');
        Iout=ver_sobel_edge(I);
    case {'ver_sobel_edge'}
        disp('Sobel Vertical Edge');
        Iout=ver_sobel_edge(I);
    case {'canny_edge'}
        disp('Canny Edge Detection');
        Iout=canny_edge(I);
    case {'motion'}
        disp('Motion');
        Iout=motion(I,20,10);
    otherwise
        disp('Unknown method.');
end
return

    function Iout = thresh(I)
        i=0;
        subplot(1,2,2); hold on;
        for thresh=1:6:254
            i=i+1;
            Iout=I < thresh;
            imshow(Iout);
            pause(0.1);
            drawnow;
            swp(i) = sum(sum(Iout))/(256*256);
            %fprintf('-> thresh = %u, swp = %f
',thresh, swp(i));
        end
        hold off
        figure, plot(swp)
        return
  
     
     function Iout = median(I,mat_max)
    % this function requires the mat_max variable which is the size of
    % matrix(row and column same dimension
    subplot(1,2,2); hold on;
    for mat_size=1:mat_max
        Iout=medfilt2(I,[mat_size,mat_size]);
        imshow(Iout,[0 255]);
        title(strcat('Size nxn Matrix=',num2str(mat_size)));
        pause(0.1);
        drawnow;
    end
    hold off
    return
    
           
    function Iout = blur_gauss(I,sigma_max)
    % this function is a rotationally symmetric gaussian low pass filter
    % HSIZE variable which is vector specifying size row and column
    % SIGMA standard deviation and must be positive
    subplot(1,2,2); hold on;
    for sigma=1:0.5:sigma_max
        Iout=imgaussfilt(I,sigma);
        imshow(Iout,[0 255]);
        title(strcat('Sigma=',num2str(sigma)));
        pause(0.8);
        drawnow;
    end
    return
    
    function Iout =log(I,size_max,sigma_max)
    % this function requires the 'sigma' and 'size' variables
    % you must create a loop for the sigma variable
    subplot(1,2,2); hold on;
    for sigma=0.1:0.1:sigma_max
        for size=1:size_max
            H=fspecial('log',size, sigma);
            Iout=imfilter(I,H,'replicate');
            imshow(Iout,[0 255]);
            title(strcat('Sigma=',num2str(sigma),'  Size=',num2str(size)));
            pause(0.1);
            drawnow;
        end
    end
    return
    
     function Iout = blur_laplace(I,alpha_max)
    % 3x3 filter this function requires the 'alpha' variable which is the
    % shape of the laplacian and is in the range 0-1
       subplot(1,2,2); hold on;
    for alpha=0.01:0.05:alpha_max
        H=fspecial('laplacian',alpha);
        Iout=imfilter(I,H,'replicate');
        imshow(Iout);
        title(strcat('Alpha=',num2str(alpha)));
        pause(0.2);
        drawnow;
    end
    return
                    
    function Iout = unsharp(I,radius_max,amount_max)
    % filter used as part of unsharp masking.
    % Radius - Specifies the standard deviation of the Gaussian lowpass
    % filter used as part of unsharp masking. This value controls the size 
    % of the region around the edge pixels that is affected by sharpening
    % A large value sharpens wider regions around the edges, whereas a small 
    % value sharpens narrower regions around edges. Default value is 1.
 
    % Amount - Specifies the strength of the sharpening effect. A higher
    % value leads to larger increase in the contrast of the sharpened pixels. 
    % Typical values for this parameter are within the range [0 2], although 
    % values greater than 2 are allowed. Very large values for this parameter 
    % may create undesirable effects in the output image. Default value is 0.8.
    
    subplot(1,2,2); hold on;
    i=0;
    for value=0.1:0.2:amount_max
        for radius=0.1:0.2:radius_max
            Iout=imsharpen(I,'Radius',radius,'Amount',value);
            imshow(Iout,[0 255]);
            title(strcat('Radius=',num2str(radius),'  Value=',num2str(value)));
            pause(0.1);
            drawnow;
        end
    end;
    return
    
    
    function Iout = blur_disk(I,max_radius)
    % simple bluring using a circular averaging filter (pillbox) 
    % within the square matrix of side 2*RADIUS+1.
    % The default RADIUS is 5.
    subplot(1,2,2); hold on;
    for radius=1:0.1:max_radius
        H=fspecial('disk',radius);
        Iout=imfilter(I,H,'replicate');
        imshow(Iout,[0 255]);
        title(strcat('Radius=',num2str(radius)));
        pause(0.1);
        drawnow;
    end;
    return

                        
    function Iout = ver_sobel_edge(I)
    % simple horizontal edge emphasizing display
    % returns 3-by-3 filter that emphasizes
    % horizontal edges utilizing the smoothing effect by approximating a
    % vertical gradient. If you need to emphasize vertical edges, transpose
    % the filter H: H'.  [1 2 1;0 0 0;-1 -2 -1].
    subplot(1,2,2); hold on;
    H=fspecial('sobel');
    Iout=imfilter(I,H','replicate');
    title('Sobel Vertical Edge Emphasizing');
    imshow(Iout,[0 255]);
    pause(0.3);
    drawnow;
    return
    
    function Iout = hor_sobel_edge(I)
    % See vertical Sobel 
    subplot(1,2,2); hold on;
    H=fspecial('sobel');
    Iout=imfilter(I,H,'replicate');
    title('Sobel Horizontal Edge Emphasizing');
    imshow(Iout,[0 255]);
    pause(0.3);
    drawnow;
    return
                            
     function Iout = hor_prewitt_edge(I)
     % simple horizontal edge emphasizing display
     % returns 3-by-3 filter that emphasizes
     % horizontal edges by approximating a vertical gradient. If you need to
     % emphasize vertical edges, transpose the filter H: H'.
     % [1 1 1;0 0 0;-1 -1 -1].
     subplot(1,2,2); hold on;
     H=fspecial('prewitt');
     Iout=imfilter(I,H,'replicate');
     title('Prewitt Horizontal Edge Emphasizing');
     imshow(Iout,[0 255]);
     pause(0.3);
     drawnow;
     return
                 
     
     function Iout = ver_prewitt_edge(I)
     % simple vertical edge emphasizing display see ho edgerizontal Prewitt
     subplot(1,2,2); hold on;
     H=fspecial('prewitt');
     Iout=imfilter(I,H','replicate');
     title('Prewitt Vertical Edge Emphasizing');
     imshow(Iout,[0 255]);
     pause(0.3);
     drawnow;
     return
     
     function Iout = canny_edge(I)
     % Canny edge emphasizing display
     subplot(1,2,2); hold on;
     Iout = edge(I,'canny');
     imshow(Iout);  
     pause(0.1)
     drawnow
     return
     
     function Iout = motion(I,len_max,theta_max)
     % simple bluring using a circular averaging filter (pillbox)
     subplot(1,2,2); hold on;
     for len=1:len_max
         for theta=0:5:theta_max
             H=fspecial('motion',len,theta);
             Iout=imfilter(I,H,'replicate');
             imshow(Iout,[0 255]);
             title(strcat('Len=',num2str(len),'  Theta=',num2str(theta)));
             pause(0.1);
             drawnow;
         end
     end;
     return