blockproc in matlab image processing

hi fellas, iam pursuing my proj in my masters. got a bug here .iam just planning to use my own function (with 2 input and 1 output arguments ) with blockproc fn but then it shows the following error " Cannot combine values of class double with struct" . it is showing error fr the following line "sq1=gsubtract(ca2,ecA);" in my function. pleas help me ..

thanks in advance

[Matt J]

Help us help you by showing your code.

[JK_1989]

sure :-) my function which i wanna interface with blockproc is

fun ction [clm,rv2,df] = estmat_2b(ecA,cv1,rv2)

[~,nh]=size(ecA);
for i=1:nh
    q=1;
for stp1=1:300;

if(q~=1)
   cv1(i,1)=cv1(i,1) + 0.01;
end
   vq1(i,1)=cv1(i,1);
[ca2]=estmat(cv1,rv2,nh,i);
sq1=gsubtract(ca2,ecA);

          e(i,q)=sum(sum(sq1.*sq1));

      e3(i,q)=e(i,q);

     vv12(i,q)=cv1(i,1);
     cv12(i,1)=vq1(i,1);
     if(stp1==300)
     df=min(e(i,:));
     [row col]=find(e(i,:)==df);
     colm=min(col);
     cv1(i,1)=vv12(i,colm);
     end
       q=q+1;

end

end

clm=cv1;
e11=e;

end

[JK_1989]

my main function is

function [outp1,outp2] = blk_itrn(inp1,ecA)

i = 5; v1=zeros(i,1); v2=zeros(i,1); for fn=1:5;

v22=ones(i,1); v11=ones(i,1);

for i=1:1;

func1 = @(block) estmat_2b(block,v1,v22); outp1 = blockproc(inp1,[i,i],func1);

func2 = @(block) estmat_3b(block,v11,v2); outp2 = blockproc(inp1,[i,i],func2);

end

end

[JK_1989]

sir,

generally , can i use my own defined fn with blockproc.....?

can that fn hav more than one input or output arguments

[Image Analyst]

Yes, you can. That's exactly what I show you how to do in my demo below.

[JK_1989]

well sir, thanks a lot . i wil refer to that n wil get back to u , sir..

Answer 1

[Image Analyst]

Here's demo of two different ways of using it.

% Demo of blockproc in two different ways.
% One uses an anonymous function to return a block of pixels
% the same size as the sliding window block.
% The other uses a custom written function to return a
% single value for each slinding window position.
function blockproc_demo()
try
  clc; % Clear the command window.
  close all; % Close all figures (except those of imtool.)
  workspace; % Make sure the workspace panel is showing.
  fontSize = 20;

  % Change the current folder to the folder of this m-file.
  if(~isdeployed)
    cd(fileparts(which(mfilename)));
  end

  % Read in standard MATLAB demo image.
  grayImage = imread('cameraman.tif');
  [rows columns numberOfColorChannels] = size(grayImage);
  % Display the original image.
  subplot(2, 2, 1);
  imshow(grayImage, []);
  caption = sprintf('Original Image\n%d by %d pixels', ...
  rows, columns);
  title(caption, 'FontSize', fontSize);
  % Enlarge figure to full screen.
  set(gcf, 'Position', get(0,'Screensize'));
  set(gcf, 'name','Image Analysis Demo', 'numbertitle','off')

  % Block process the image.
  windowSize = 3;
  % Each 3x3 block will get replaced by one value.
  % Output image will be smaller by a factor of windowSize.
  myFilterHandle = @myFilter;
  blockyImage = blockproc(grayImage,[windowSize windowSize], myFilterHandle);
  [rowsP columnsP numberOfColorChannelsP] = size(blockyImage);

  % Display the processed image.
  % It is smaller, but the display routine imshow() replicates
  % the image so that it looks bigger than it really is.
  subplot(2, 2, 2);
  imshow(blockyImage, []);
  caption = sprintf('Image Processed in %d by %d Blocks\n%d by %d pixels\nCustom Box Filter', ...
  windowSize, windowSize, rowsP, columnsP);
  title(caption, 'FontSize', fontSize);

  % Now let's do it an alternate way where we use an anonymous function.
  % We'll take the standard deviation in the blocks.
  windowSize = 8;
  myFilterHandle2 = @(block_struct) ...
  std2(block_struct.data) * ones(size(block_struct.data));
  blockyImageSD = blockproc(grayImage, [windowSize windowSize], myFilterHandle2);
  [rowsSD columnsSD numberOfColorChannelsSD] = size(blockyImageSD);
  subplot(2, 2, 4);
  imshow(blockyImageSD, []);
  caption = sprintf('Image Processed in %d by %d Blocks\n%d by %d pixels\nAnonymous Standard Deviation Filter', ...
  windowSize, windowSize, rowsSD, columnsSD);
  title(caption, 'FontSize', fontSize);

  % Note: the image size of blockyImageSD is 256x256, NOT smaller.
  % That's because we're returning an 8x8 array instead of a scalar.

  uiwait(msgbox('Done with demo'));
  catch ME
    errorMessage = sprintf('Error in blockproc_demo():\n\nError Message:\n%s', ME.message);
    uiwait(warndlg(errorMessage));
  end
  return;

% Takes one 3x3 block of image data and multiplies it
% element by element by the kernel and
% returns a single value.
function singleValue = myFilter(blockStruct)
  try
    % Assign default value.
    % Will be used near sides of image (due to boundary effects),
    % or in the case of errors, etc.
    singleValue = 0;

    % Create a 2D filter.
    kernel = [0 0.2 0; 0.2 0.2 0.2; 0 0.2 0];
    % kernel = ones(blockStruct.blockSize); % Box filter.

    % Make sure filter size matches image block size.
    if any(blockStruct.blockSize ~= size(kernel))
      % If any of the dimensions don't match.
      % You'll get here near the edges,
      % if the image is not a multiple of the block size.
      % warndlg('block size does not match kernel size');
      return;
    end
    % Size matches if we get here, so we're okay.

    % Extract our block out of the structure.
    array3x3 = blockStruct.data;

    % Do the filtering. Multiply by kernel and sum.
    singleValue = sum(sum(double(array3x3) .* kernel));

  catch ME
    % Some kind of problem...
    errorMessage = sprintf('Error in myFilter():\n\nError Message:\n%s', ME.message);
    % uiwait(warndlg(errorMessage));
    fprintf(1, '%s\n', errorMessage);
  end
  return;