Comments on: Nonlinear operations using imfilter http://blogs.mathworks.com/steve/2008/07/07/nonlinear-operations-using-imfilter/ Steve Eddins manages the Image & Geospatial development team at <a href="http://www.mathworks.com/">The MathWorks</a> and coauthored <a href="http://www.mathworks.com/support/books/book5291.html?category=-1&language=-1">Digital Image Processing Using MATLAB</a>. He writes here about image processing concepts, algorithm implementations, and MATLAB.<br><br><img> Mon, 23 Nov 2009 08:19:38 +0000 http://wordpress.org/?v=2.3.1 By: Steve http://blogs.mathworks.com/steve/2008/07/07/nonlinear-operations-using-imfilter/#comment-20860 Steve Thu, 10 Jul 2008 16:58:19 +0000 http://blogs.mathworks.com/steve/2008/07/07/nonlinear-operations-using-imfilter/#comment-20860 Francisco—At last count, there were 13,273,474 journal and conference papers describing different methods of edge detection. :-) Think about regions of differing texture. The local standard deviation operator would have a relatively higher response in regions of "busier" texture, and it would have a relatively lower response in "smoother" regions. This is different than what most people think an edge detector does. Francisco—At last count, there were 13,273,474 journal and conference papers describing different methods of edge detection. :-)

Think about regions of differing texture. The local standard deviation operator would have a relatively higher response in regions of “busier” texture, and it would have a relatively lower response in “smoother” regions. This is different than what most people think an edge detector does.

]]> By: francisco http://blogs.mathworks.com/steve/2008/07/07/nonlinear-operations-using-imfilter/#comment-20859 francisco Wed, 09 Jul 2008 16:56:05 +0000 http://blogs.mathworks.com/steve/2008/07/07/nonlinear-operations-using-imfilter/#comment-20859 Hi Steve, You mention that the local standard deviation technique measures the 'business' of an image. How is this different, if at all, from edge detection? It looks like your first example does a really amazing job at finding edges, albeit they are rather thick. thanks -francisco Hi Steve,

You mention that the local standard deviation technique measures the ‘business’ of an image. How is this different, if at all, from edge detection? It looks like your first example does a really amazing job at finding edges, albeit they are rather thick.

thanks
-francisco

]]> By: Steve http://blogs.mathworks.com/steve/2008/07/07/nonlinear-operations-using-imfilter/#comment-20854 Steve Mon, 07 Jul 2008 15:58:31 +0000 http://blogs.mathworks.com/steve/2008/07/07/nonlinear-operations-using-imfilter/#comment-20854 Luca—Thanks for submitting your code to the File Exchange! Luca—Thanks for submitting your code to the File Exchange!

]]> By: Luca Balbi http://blogs.mathworks.com/steve/2008/07/07/nonlinear-operations-using-imfilter/#comment-20853 Luca Balbi Mon, 07 Jul 2008 15:21:18 +0000 http://blogs.mathworks.com/steve/2008/07/07/nonlinear-operations-using-imfilter/#comment-20853 This very same "sum of squares minus sqaure of sum" consideration drove me to re-implement the Kuwahara nonlinear filter in a faster way, though I did not use imfilter but just straightforward convolution, as I did not want the Image Processing Toolbox to be needed: http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=15027&objectType=FILE Nice example by the way Steve! And thanks for pointing to the stdfilt function. This very same “sum of squares minus sqaure of sum” consideration drove me to re-implement the Kuwahara nonlinear filter in a faster way, though I did not use imfilter but just straightforward convolution, as I did not want the Image Processing Toolbox to be needed:

http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=15027&objectType=FILE

Nice example by the way Steve! And thanks for pointing to the stdfilt function.

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