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Image Recovery Using APOCS
Abstract
The proposed algorithm is a technique for recovering block based images of size 4 x 4. The algorithm is based on orthogonal projections onto constraint sets in a Hilbert space. For recovering the lost blocks, a total of 8N vectors are extracted from the surrounding area of an N X N missing blocks. From these vectors the best matching spatial information for the missing block is extracted. The vectors are used to find the highly correlated information relating to the lost pixels. To assure continuity with the surrounding undamaged area, convex constraints are formulated. Adherance to these sets is imposed using alternating projections.Characteristics of the results are those of the “LENA” image. The image quality is measured with the peak signal to noise ratio (PSNR)and it is 39.5952db for the recovered image with the proposed technique.
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References
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