Affiliation:
1. College of Software Engineering, Taiyuan University of Technology, Taiyuan 030024, P. R. China
2. College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, P. R. China
Abstract
This paper proposes a lossless encryption–compression algorithm for large-scale remote sensing images. Firstly, the red, green and blue components of color image are compressed by a lossless predictive encoding. Then, the lifting wavelet transform (LWT) is used to decompose the encoding results. And a new Rubik’s cube transformation is introduced to scramble the decomposed coefficients, which uses the chaotic sequence generated by 2D Cubic–Chebyshev map (2D-CCM). The initial values of 2D-CCM are obtained from the chi-square test values of the three components, which leads to the algorithm related to the plaintext image. After that, the scrambling coefficients are thresholding, and the position sequences generated in the process are encrypted and compressed by the proposed encrypted run-length encoding (E-RLE). The processed coefficients are further compressed by Huffman encoding. At the end, the final results are obtained by a novel helix diffusion which is related to the chaotic sequence. Experimental results show that, this algorithm achieves higher lossless compression ratio with lower time complexity, and the encryption scheme has higher security.
Publisher
World Scientific Pub Co Pte Ltd
Subject
Applied Mathematics,Modeling and Simulation,Engineering (miscellaneous)
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献