Symmetrical predictor structure based integrated lossy, near lossless/lossless coding of images

Prediction based algorithms reported in the literature are not able to integrate lossy and near-lossless/lossless coding and uses only causal pixels (non-symmetrical predictor structure) for prediction. A non-symmetrical predictor structure, however, is not able to efficiently adapt near the intensi...

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Bibliographic Details
Published in2014 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 2293 - 2296
Main Authors Jakhetiya, Vinit, Au, Oscar C., Jaiswal, Sunil Prasad, Luheng Jia, Mittal, Gaurav
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2014
Subjects
Bit rate
Computational Complexity
Decoding
Image coding
Image edge detection
Image reconstruction
Near-lossless and Lossless Image Compression
Prediction algorithms
Symmetrical Predictor Structure
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Summary:Prediction based algorithms reported in the literature are not able to integrate lossy and near-lossless/lossless coding and uses only causal pixels (non-symmetrical predictor structure) for prediction. A non-symmetrical predictor structure, however, is not able to efficiently adapt near the intensity varying areas, which results into poor prediction. Hence, we propose a novel two-stage algorithm for lossy, near lossless/lossless compression using a symmetrical predictor structure is proposed. In the first stage, the proposed algorithm encodes and decodes the given image using the JPEG-2000 standard algorithm (lossy coding). This JPEG-2000 decoded image in the first stage, enables us to use the symmetrical predictor (using both causal and non-causal pixels) for prediction in the second stage. A performance evaluation shows that our algorithm is significantly better in terms of compression performance as compared to some of the computationally complex methods.
ISSN:0271-4302
2158-1525
DOI:10.1109/ISCAS.2014.6865629