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Compressive Sensing based Image Compression and Recovery


Author(s):

Dr Renuka Devi SM , GNITS

Keywords:

Compressive Sensing, L1 Optimization, Tree Structured Wavelet (TSW)

Abstract:

Compressive sensing is a new paradigm in image acquisition and compression. The CS theory promises recovery of images even if the sampling rate is far below the nyquist rate. This enables better acquisition and easy compression of images, which is more advantageous when the resources at the sender side are scarce. This paper shows the CS based compression and two recovery two methods i.e., l1 optimization and TSW CS recovery. Experimental results show that CS provides better compression, and TSWCS provides better recovery with less relative error recovery than l1 optimization. It is also observed that use of increased measurements leads to reduced error.


Other Details:

Manuscript Id :IJSTEV3I5051
Published in :Volume : 3, Issue : 5
Publication Date: 01/12/2016
Page(s): 28-33
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