Tuesday, October 23, 2012

SCoBeP: Dense Image Registration using Sparse Coding and Belief Propagation - implementation -

Found through a discussion on the LinkedIn Compressive Sensing group
SCoBeP: Dense Image Registration using Sparse Coding and Belief Propagation by Nafise Barzigar, Amin mohammad Roozgard, Samuel Cheng, Pramode Verma. The abstract reads:
Image registration as a basic task in image processing has been studied widely in the literature. It is an important preprocessing step in various applications such as medical imaging, super resolution, and remote sensing. In this paper, we proposed a novel dense registration method based on sparse coding and belief propagation. We used image blocks as features, and then we employed sparse coding to find a set of candidate points. To select optimum matches, belief propagation was subsequently applied on these candidate points. Experimental results show that the proposed approach is able to robustly register scenes and is competitive as compared to high accuracy optical flow [1], and SIFT  flow [2].
The implementation of SCoBeP is here.





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3 comments:

ernestinis said...

So SCoBeP complexity is very high O(m^4+...) m-pixel count?

Raingo Lee said...

It's ugly to provide *.p only and some of the *.p with filename untitled.p

Anonymous said...

Wow, It is Nice job!

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