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Image compression and encryption based on wavelet  transform and chaos
  H. Gao,  W. Zeng
  College of Information Science & Engineering, Hunan International  Economics University,  Changsha 410205, China
 PDF, 1040 kB
  PDF, 1040 kB
DOI: 10.18287/2412-6179-2019-43-2-258-263
Страницы: 258-263.
Аннотация:
  With the rapid  development of network technology, more and more digital images are transmitted  on the network, and gradually become one important means for people to access  the information. The security problem of the image information data  increasingly highlights and has become one problem to be attended. The current  image encryption algorithm basically focuses on the simple encryption in the  frequency domain or airspace domain, and related methods also have some  shortcomings. Based on the characteristics of wavelet transform, this paper  puts forward the image compression and encryption based on the wavelet  transform and chaos by combining the advantages of chaotic mapping. This method  introduces the chaos and wavelet transform into the digital image encryption  algorithm, and transforms the image from the spatial domain to the frequency  domain of wavelet transform, and adds the hybrid noise to the high frequency  part of the wavelet transform, thus achieving the purpose of the image  degradation and improving the encryption security by combining the encryption  approaches in the spatial domain and frequency domain based on the chaotic  sequence and the excellent characteristics of wavelet transform. Testing  experiments show that such algorithm reduces the memory consumption and  implements the complexity, not only can decrease the key spending and compress  the time spending, but also can improve the quality of decoded and  reconstructed image, thus showing good encryption features with better  encryption effect.
Ключевые слова:
  image encryption,  wavelet coefficient, chaotic system.
Цитирование: 
Gao H, Zeng W. Image  compression and encryption based on wavelet transform and chaos. Computer  Optics 2019; 43(2): 258-263. DOI: 10.18287/2412-6179-2019-43-2-258-263.
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