Set theoretic compression with an application to image coding

We show that the complete information that is available after an image has been encoded is not just an approximate quantized image version, but a whole set of consistent images that contains the original image by necessity. From this starting point, we develop a set of tools to design a new class of encoders for image compression, based on a set decomposition and recombination of image features. As an initial validation, we show the results of an experiment where these tools are used to modify the encoding process of block discrete cosine transform (DCT) coding in order to yield less blocking artifacts

Image information restoration based on long-range correlation

2001-2002 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Multiple Selection Extrapolation for Improved Spatial Error Concealment

This contribution introduces a novel signal extrapolation algorithm and its application to image error concealment. The signal extrapolation is carried out by iteratively generating a model of the signal suffering from distortion. Thereby, the model results from a weighted superposition of two-dimensional basis functions whereas in every iteration step a set of these is selected and the approximation residual is projected onto the subspace they span. The algorithm is an improvement to the Frequency Selective Extrapolation that has proven to be an effective method for concealing lost or distorted image regions. Compared to this algorithm, the novel algorithm is able to reduce the processing time by a factor larger than three, by still preserving the very high extrapolation quality

Error resilient image transmission using T-codes and edge-embedding

Current image communication applications involve image transmission over noisy channels, where the image gets damaged. The loss of synchronization at the decoder due to these errors increases the damage in the reconstructed image. Our main goal in this research is to develop an algorithm that has the capability to detect errors, achieve synchronization and conceal errors.;In this thesis we studied the performance of T-codes in comparison with Huffman codes. We develop an algorithm for the selection of best T-code set. We have shown that T-codes exhibit better synchronization properties when compared to Huffman Codes. In this work we developed an algorithm that extracts edge patterns from each 8x8 block, classifies edge patterns into different classes. In this research we also propose a novel scrambling algorithm to hide edge pattern of a block into neighboring 8x8 blocks of the image. This scrambled hidden data is used in the detection of errors and concealment of errors. We also develop an algorithm to protect the hidden data from getting damaged in the course of transmission

Fast block-based image restoration employing the improved best neighborhood matching approach

2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe