Sliding window minimum and maximum filter - MATLAB Answers

link管理

链接快照平台

输入网页链接，自动生成快照
标签化管理网页链接

相关文章推荐

暴躁的人字拖 · 经常收到“积分到期兑换”短信？ ...· 1 周前 ·

一直单身的匕首 · 孙长颢教授入选国家百千万人才工程-哈尔滨医科 ...· 3 周前 ·

气势凌人的香菇 · 关于合理规划市内道路交通提案 ...· 5 月前 ·

伤情的感冒药 · EPPLUS中单元格的属性_epplus ...· 5 月前 ·

火爆的铅笔 · 2023年杨浦区公办幼儿园入园相关信息· 10 月前 ·

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter

I'm trying to apply a sliding window minimum and maximum filter to an image of a certain window size. Actually, I'm trying to find the optimum window size for it. But I really haven't gotten the hang of it. I presume that I should be using blockproc to implement the sliding window, but not really sure how to find the maximum and minimum filter. As to the implementation itself, should I use loops to slide the window across the entire area of the image ?

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102056

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102059

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_114677

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_114682

From the description "A two-element vector, [V H], specifying the amount of border pixels to add to each block. The function adds V rows above and below each block and H columns left and right of each block." it looks like you'd have a windowSize of 1 so that it moves over in jumps of 1 pixel each time, but the 'BorderSize' would be half your window width so that it includes more than just the one pixel it's centered on. So if you wanted a 5 by 5 window, you'd set a windowSize of 1 and a BorderSize of 2. I think - I haven't tried it.

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_114698

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#answer_60377

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102057

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102058

I did, above. At least I showed how to get them. How you USE them afterwards is up to you. If you need a more complete demo, see below. In that, I just "use" them by simply displaying them in the image.

      
        clc;
       
        % Clear the command window.
       
        close
       
        all
       
        ;
       
        % Close all figures (except those of imtool.)
       
        imtool
       
        close all
       
        ;
       
        % Close all imtool figures.
       
        clear;
       
        % Erase all existing variables.
       
        workspace;
       
        % Make sure the workspace panel is showing.
       
        format
       
        longg
       
        ;
       
        format
       
        compact
       
        ;
       
        fontSize = 20;
       
        % Change the current folder to the folder of this m-file.
       
        if
       
        (~isdeployed)
       
        cd(fileparts(which(mfilename)));
       
        end
       
        % Check that user has the Image Processing Toolbox installed.
       
        hasIPT = license(
       
        'test'
       
        ,
       
        'image_toolbox'
       
        );
       
        if
       
        ~hasIPT
       
        % User does not have the toolbox installed.
       
        message = sprintf(
       
        'Sorry, but you do not seem to have the Image Processing Toolbox.\nDo you want to try to continue anyway?'
       
        );
       
        reply = questdlg(message,
       
        'Toolbox missing'
       
        ,
       
        'Yes'
       
        ,
       
        'No'
       
        ,
       
        'Yes'
       
        );
       
        if
       
        strcmpi(reply,
       
        'No'
       
        )
       
        % User said No, so exit.
       
        return
       
        ;
       
        end
       
        end
       
        % Read in a standard MATLAB gray scale demo image.
       
        folder = fullfile(matlabroot,
       
        '\toolbox\images\imdemos'
       
        );
       
        baseFileName =
       
        'cameraman.tif'
       
        ;
       
        % Get the full filename, with path prepended.
       
        fullFileName = fullfile(folder, baseFileName);
       
        % Check if file exists.
       
        if
       
        ~exist(fullFileName,
       
        'file'
       
        )
       
        % File doesn't exist -- didn't find it there.  Check the search path for it.
       
        fullFileName = baseFileName;
       
        % No path this time.
       
        if
       
        ~exist(fullFileName,
       
        'file'
       
        )
       
        % Still didn't find it.  Alert user.
       
        errorMessage = sprintf(
       
        'Error: %s does not exist in the search path folders.'
       
        , fullFileName);
       
        uiwait(warndlg(errorMessage));
       
        return
       
        ;
       
        end
       
        end
       
        grayImage = imread(fullFileName);
       
        % Get the dimensions of the image.
       
        % numberOfColorBands should be = 1.
       
        [rows columns numberOfColorBands] = size(grayImage);
       
        % Display the original gray scale image.
       
        subplot(2, 2, 1);
       
        imshow(grayImage, []);
       
        title(
       
        'Original Grayscale Image'
       
        ,
       
        'FontSize'
       
        , fontSize);
       
        % Enlarge figure to full screen.
       
        set(gcf,
       
        'units'
       
        ,
       
        'normalized'
       
        ,
       
        'outerposition'
       
        ,[0 0 1 1]);
       
        % Give a name to the title bar.
       
        set(gcf,
       
        'name'
       
        ,
       
        'Demo by ImageAnalyst'
       
        ,
       
        'numbertitle'
       
        ,
       
        'off'
       
        )
       
        % Let's compute and display the histogram.
       
        [pixelCount grayLevels] = imhist(grayImage);
       
        subplot(2, 2, 2);
       
        bar(pixelCount);
       
        grid
       
        on
       
        ;
       
        title(
       
        'Histogram of original image'
       
        ,
       
        'FontSize'
       
        , fontSize);
       
        xlim([0 grayLevels(end)]);
       
        % Scale x axis manually.
       
        % Compute the local max and min images:
       
        localMinImage = imerode(grayImage, true(3));
       
        localMaxImage = imdilate(grayImage, true(3));
       
        % Display them.
       
        subplot(2, 2, 3);
       
        imshow(localMinImage, []);
       
        title(
       
        'Local Min (eroded) Image'
       
        ,
       
        'FontSize'
       
        , fontSize);
       
        subplot(2, 2, 4);
       
        imshow(localMaxImage, []);
       
        title(
       
        'Local Max (dilated) Image'
       
        ,
       
        'FontSize'
       
        , fontSize);

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102060

Basically, I am attempting to correct an image with uneven illumination by applying a sliding window minimum filter on the image and then finding the illumination or shading function, by applying sliding window maximum filter on on the output of the minimum filter. Later, I'm trying to find the 'perfect image' by dividing the original image with the illumination function.

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102064

Doing a max filter on the output of the min filter is called a morphological opening and is done by imopen(). It is not a way to get the illumination pattern that I've ever heard of. I do background correction all the time and this would not be a good way of getting the background unless your background was uniform and had small light-colored dust on it. But even then, there are flaws with that method such that you will increase the noise and have quantization/posterization errors. Do you have a uniform background that you can image? Or all you have is the image with your scene and illumination combined? If, unfortunately, you have the latter case, you can either try homomorphic filtering (basically assuming the light pattern is a very low pass filtered version of your scene) or try to find "holes" in your scene that is pure background and then try to fit a nice smooth model, like a 2D polynomial, to them. Finally, division is the right way to do it in most cases . For certain other cases (radiology and fluorescence) you should do subtraction. Do the math and you'll see why. Upload an image if you want further advice.

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102069

Its an assignment that I've been asked to do and that's the method that has been specified. It states that an image g(x,y) can be modeled as the product of a "perfect image" denoted by f(x,y) and an illumination function l(x,y). i.e g(x,y) = f(x,y) * l(x,y) So the assignment is to find l(x,y) using the method that I've stated in my earlier response. To implement a minimum sliding window filter on g(x,y) and then implementing a sliding window maximum filter on the output of the minimum filter. This way, I'll find l(x,y) and then find f(x,y) by dividing g(x,y) by l(x,y). I've attached the image which is basically a modified rice.tif image. https://dl.dropbox.com/u/793037/lab2.tif

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102073

If the rice image is like the MATLAB rice image with a gradient background, then doing an opening would give you just the dark gradient background because the erosion eats away the rice and then the closing gets the dark things back to their original size. You can do that, but that is exactly the situation I was saying would give you amplified image noise and posterization artifacts. It might be okay in certain situations, but not those where you need high accuracy. You can do this assignment in two lines. One call to imopen(), and another to divide the images. Then of course some more stuff to fancy it up like display the image(s), give them titles, etc.

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102076

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102079

      
        clc;
       
        % Clear the command window.
       
        close
       
        all
       
        ;
       
        % Close all figures (except those of imtool.)
       
        imtool
       
        close all
       
        ;
       
        % Close all imtool figures.
       
        clear;
       
        % Erase all existing variables.
       
        workspace;
       
        % Make sure the workspace panel is showing.
       
        format
       
        longg
       
        ;
       
        format
       
        compact
       
        ;
       
        fontSize = 13;
       
        % Read in a standard MATLAB gray scale demo image.
       
        folder = fullfile(matlabroot,
       
        '\toolbox\images\imdemos'
       
        );
       
        baseFileName =
       
        'rice.png'
       
        ;
       
        % Get the full filename, with path prepended.
       
        fullFileName = fullfile(folder, baseFileName);
       
        % Check if file exists.
       
        if
       
        ~exist(fullFileName,
       
        'file'
       
        )
       
        % File doesn't exist -- didn't find it there.  Check the search path for it.
       
        fullFileName = baseFileName;
       
        % No path this time.
       
        if
       
        ~exist(fullFileName,
       
        'file'
       
        )
       
        % Still didn't find it.  Alert user.
       
        errorMessage = sprintf(
       
        'Error: %s does not exist in the search path folders.'
       
        , fullFileName);
       
        uiwait(warndlg(errorMessage));
       
        return
       
        ;
       
        end
       
        end
       
        grayImage = imread(fullFileName);
       
        % Get the dimensions of the image.
       
        % numberOfColorBands should be = 1.
       
        [rows columns numberOfColorBands] = size(grayImage);
       
        % Display the original gray scale image.
       
        subplot(2, 2, 1);
       
        imshow(grayImage, []);
       
        title(
       
        'Original Grayscale Image'
       
        ,
       
        'FontSize'
       
        , fontSize);
       
        % Do an opening to get the background.
       
        % This is not a good method for this image.
       
        openedImage = imopen(grayImage, true(13));
       
        subplot(2, 2, 2);
       
        imshow(openedImage, []);
       
        title(
       
        'Background Image'
       
        ,
       
        'FontSize'
       
        , fontSize);
       
        % Divide them
       
        backgroundCorrected = grayImage ./ openedImage;
       
        subplot(2, 2, 3);
       
        imshow(backgroundCorrected, []);
       
        title(
       
        'Background-corrected Image'
       
        ,
       
        'FontSize'
       
        , fontSize);

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102093

Thanks for that. It works exactly like I want it to. But suppose, if both my original image and illumination function are double precision values and if I'd want my output image also to be a double precision value, wouldn't my resultant image have minimum and maximum values out of range rather than between [0 1] ?

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_102102

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_209704

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_209723

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_209729

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_209823

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_209877

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_210677

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_210697

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#answer_60376

I would just use a for-loop to do 2 separable passes. BLOCKPROC can't take advantage of the separable nature of the max/min filter:

      
        A=rand(100);
       
        window=3;
       
        [m,n]=size(A);
       
        B=A;
       
        for
       
        ii=1:m+1-window
       
        B(ii,:)=max(A(ii:ii+window-1,:),[],1);
       
        end
       
        for
       
        ii=1:n+1-window
       
        B(:,ii)=max(B(:,ii:ii+window-1),[],2);
       
        end

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#comment_209730

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#answer_134237

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#answer_156514

i want to apply a sliding window minimum filter on input image I and obtain Imin and also apply sliding window maximum filter on Imin to obtain Imax : the following is code

      
        N=1;
       
        Imin=ordfilt2(I, 1, true(N));
       
        N=10;
       
        Imax = ordfilt2(Imin, N*N, true(N));

here i assume N as window size... but i am confused as how should i take N for minimum filter and again N for maximum filter?

https://www.mathworks.com/matlabcentral/answers/49368-sliding-window-minimum-and-maximum-filter#answer_271165

      
        function
       
        [minVals,maxVals] = minmaxfilt1(vector,nhoodSz)
       
        vector = vector(:);
       
        if
       
        nhoodSz < 3 || ~floor(mod(nhoodSz,2))
       
        error(
       
        'nhoodSz must be odd scalar'
       
        );
       
        end
       
        minVals = min(conv2(vector,eye(nhoodSz)),[],2);
       
        maxVals = max(conv2(vector,eye(nhoodSz)),[],2);
       
        minVals = minVals(((nhoodSz-1)/2)+1: end- ((nhoodSz-1)/2));
       
        maxVals = maxVals(((nhoodSz-1)/2)+1: end - ((nhoodSz-1)/2));
       
        end

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!