A Novel Lossless Image Compression Algorithm using Arithmetic Modulo Operation

Pattanaik, Sunil Kumar; Mahapatra, Kamalakanta; Panda, Ganapati

doi:10.1109/iccis.2006.252303

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…This is very much useful for those images where the information content is very large i.e. redundant data is very less [3].…”

Section: Resultsmentioning

confidence: 99%

“…This technique is designed for high quality still image compression, especially Peak Signal to Noise Ratio (PSNR) value above 34 [3]. This algorithm is most applicable for those images where lossy compression is avoided such as medical and scientific images [3]. The encoding and decoding procedure is very fast.…”

Section: Related Workmentioning

confidence: 99%

“…A NEW IMAGE COMPRESSION SCHEME USING REPEAT REDUCTION AND ARITHMETIC CODING By exploiting the methods proposed by S. K. Pattanaik [3] and by S. C. Huang et ale [1] we proposed an image compression scheme using repeat reduction and arithmetic coding, which gives better compression ratio. In this scheme we use compression ratio as the major measurement issue of performance for lossless image compression.…”

Section: IIImentioning

confidence: 99%

“…The difference between two adjacent pixel values is called neighboring difference [3]. The neighbor pixels usually represent the same object so that the values of the pixels are similar or same.…”

Section: IIImentioning

confidence: 99%

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A new image compression scheme using repeat reduction and arithmetic coding

Islam

Baki

Palash

2009

2009 12th International Conference on Computers and Information Technology

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Based on some simple arithmetic operation, an efficient lossless image compression technique is proposed We use repeat reduction and arithmetic coding to improve the results of compression. We get better results than Log-Exp based compression and Arithmetic modulo based compression. From the experimental results, it can be seen that the performance ofproposed method is better for all standard images. The complexity of our proposed method with respect to compression ratio has also been analyzed The proposed method is most applicable for those images where lossy compression is to be avoided

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“…This is very much useful for those images where the information content is very large i.e. redundant data is very less [3].…”

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: IIImentioning

confidence: 99%

Section: IIImentioning

confidence: 99%

See 2 more Smart Citations