A Comparative Analysis of Compression Techniques – The Sparse Coding and BWT

Pradhan, Annapurna; Pati, Nibedita; Rup, Suvendu; Panda, Avipsa S.; Kanoje, Lalit

doi:10.1016/j.procs.2016.07.330

Cited by 1 publication

(1 citation statement)

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“…For many decades images compression has been most researched area because transmission and storage of images are real challenging task. The authors [5] have discussed various image compression algorithms like JPEG, JPEG 2000, BWT, and sparse coding method. The sparse approximation method with DCT and Gabor basis is used to train static over complete dictionary where dictionary elements are trained using OMP algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance analysis of compression algorithms for information security: A Review

Sharma

Batra

2018

ICST Transactions on Scalable Information Systems

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Data compression is a vital part of information security, since compressed data is much more secure and convenient to handle. Effective data compression technique creates an effective, secure, easy communicable & redundant data. There are two types of compression algorithmic techniques:-lossy and lossless. These techniques can be applied to any data format like text, audio, video or image file. The primary objective of this study was to analyse data compression techniques used for information security techniques like steganography, cryptography etc. Four each, lossy and lossless techniques are implemented and evaluated on parameters like-file size, saving percentage, time, compression ratio and speed. Detailed analysis shows that the lossy techniques performs better quantitatively whereas lossless is better qualitatively. However, lossless techniques are more effective as there is no data loss during the process. Among all, Huffman encoding outperforms other algorithms.

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Section: Literature Reviewmentioning

confidence: 99%