Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors
IEEE Transactions on Information Theory
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Concealment of damaged block transform coded images using projections onto convex sets
IEEE Transactions on Image Processing
Estimation of edge direction for block error concealment using hypothesis testing problem
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
Computer aided orthodontics measures evaluation
MACMESE'11 Proceedings of the 13th WSEAS international conference on Mathematical and computational methods in science and engineering
Orthodontics objects segmentation using region growing method and space illumination
MACMESE'11 Proceedings of the 13th WSEAS international conference on Mathematical and computational methods in science and engineering
| Hi-index | 0.00 |
In this paper we propose an algorithm for image recovery where completely lost blocks in an image/video-frame are recovered using spatial information surrounding these blocks. Our primary application is on lost regions of pixels containing textures, edges and other image features that are not readily handled by prevalent recovery and error concealment algorithms. The proposed algorithm is based on the iterative application of a generic denoising algorithm and it does not necessitate any complex preconditioning, segmentation, or edge detection steps. Utilizing locally sparse linear transforms and overcomplete denoising, we obtain good PSNR performance in the recovery of such regions. In addition to results on image recovery, the paper provides further insights into the usefulness of popular transforms like wavelets, wavelet packets, Discrete Cosine Transform (DCT) and complex wavelets in providing sparse image representations.