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Graph-cut-based compression algorithm for compressed-sensed image acquisition | IEEE Conference Publication | IEEE Xplore

Graph-cut-based compression algorithm for compressed-sensed image acquisition


Abstract:

The purpose of the paper is to find the best quantizer allocation for compressed-sensed acquired images, by using a graph-cut quantizer allocation method. The compressed ...Show More

Abstract:

The purpose of the paper is to find the best quantizer allocation for compressed-sensed acquired images, by using a graph-cut quantizer allocation method. The compressed sensed acquisition is realized in a block-based manner, using a random projection matrix, and on the obtained block measurements a graph-cut-based quantizer allocation method is applied, in order to further reduce the bitrate associated to the measurements. Finally, the quantized measurements are reconstructed using a Smooth Projected Landweber recovery method. The proposed compression method for compressed sensed acquisition shows better results when compared to JPEG2000.
Date of Conference: 23-25 April 2014
Date Added to IEEE Xplore: 12 June 2014
Electronic ISBN:978-1-4799-4874-1
Print ISSN: 2165-0608
Conference Location: Trabzon, Turkey

References

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