JOURNAL ARTICLE

Image adaptive selective encryption of vector quantization index compression

Abstract

The foremost issues with most of the existing selective encryption (SE) schemes of images are vulnerability to cryptographic and application specific attacks, reduction in the compression performance, insubstantial computational savings relative to full encryption, and lack of bit stream compliance. This paper is the first one that proposes effective schemes for joint vector quantization (VQ) based image compression and SE. We introduce an image adaptive VQ index compression algorithm suitable for SE, effectively combining remapping of indices, entropy, predictive, differential, and search order coding. We then present SE through codebook pseudorandom shuffling and block ciphering of the VQ index image bit-planes, index usage map, prediction information tables and full indices. Experimentally, the results demonstrate the improved performance and effectiveness of the proposed schemes.

Keywords:
Vector quantization Codebook Computer science Encryption Entropy encoding Algorithm Shuffling Data compression Cryptography Image compression Pseudorandom number generator Entropy (arrow of time) Bitstream Theoretical computer science Artificial intelligence Image (mathematics) Decoding methods Image processing

Metrics

4
Cited By
0.62
FWCI (Field Weighted Citation Impact)
40
Refs
0.75
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Chaos-based Image/Signal Encryption
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Algorithms and Data Compression
Physical Sciences →  Computer Science →  Artificial Intelligence

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