Steve on Image Processing with MATLAB

Image processing concepts, algorithms, and MATLAB


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R2009a – MATLAB updates

MATLAB R2009a was released earlier this month. There are several things in this release, both in MATLAB and in the Image Processing Toolbox, that I plan to write about during the next couple of weeks.

My usual practice for the MATLAB releases is to mention changes of particular interest to image processing readers, plus a few other things I'm personally interested in. Other MATLAB Central bloggers will have their own perspectives on the release; in particular, I suggest that you visit "Ken and Mike on the MATLAB Desktop" and "Loren on the Art of MATLAB."

We continue to expand the set of MATLAB computations that are multithreaded. This time around we have multithreaded implementations of fft, fft2, fftn, ifft, ifft2, and ifftn.

For users with complex scientific data sets, we now support the latest HDF 5 library, which is version 1.8.1.

For users storing very many images in a single TIFF file (thousands or tens of thousands of images per file), we have a faster way to read them. Unfortunately, I dropped the ball on getting this change properly documented. It's mentioned in the M-file help for imread, but not in the reference page and not in the release notes. So type help imread and look for the 'Info' parameter in the TIFF-specific syntaxes section. I'll write a post specifically about this topic soon.

Although I am certainly no expert on computational geometry, the topic does interest me, and it does have application to image processing. So I'm excited that the MATLAB R2009a release includes significant new capabilities in this area. Here's an excerpt from the release notes:

MATLAB includes a new object-oriented suite of computational geometry tools, together with a new underlying library called CGAL. The new library provides improved robustness, performance, and memory efficiency. The new tools are presented in three classes:

  • New class TriRep provides topological and geometric queries for triangulations in 2-D and 3-D space.
  • New class DelaunayTri provides increased functionality for Delaunay triangulation including topological and geometric queries, incremental modification, and edge constraints.
  • New class TriScatteredInterp provides fast robust scattered data interpolation and a new natural-neighbor interpolation technique.
Watch for more posts soon about changes in the Image Processing Toolbox. Some the changes have been significantly influenced by comments received on this blog!
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