NFCS 3D Techniques for Fast Recovery of Sparse Color Images
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2012, Vol 1, Issue 7
Abstract
The objective of this project is to reconstruct 3D sparse images using Non-linear Filtering Compressed Sensing (NFCS) 3D Anisotropic and 3D Isotropic techniques. Compressed Sensing is a new paradigm for signal recovery and sampling. Using proposed NFCS 3D techniques, a random mask is generated for the selected input color image using a sampling matrix. Now, a sparse image is generated for the selected 3D image. Applying Normalization, the original image will be reconstructed from the sparse color image in iterations. The obtained reconstructed 3D image will be filtered using an appropriate adaptive non-linear filter in proposed NFCS 3D techniques. The output parameters like PSNR, Normalized Factor, and CPU Elapsed time will be calculated and compared along with simulation results of 2D techniques. The results obtained using proposed techniques will confirm that these possess properties of efficiency, stability, low computational cost, fast recovery of 3D images in few seconds and its performance is competitive with those of state of art algorithms.
Authors and Affiliations
Srinivasareddy Putluri, Dr. Shaik Meeravali
Keywords
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