激光技术, 2018, 42 (6): 733, 网络出版: 2018-12-25   

小波变换和菲涅耳变换的多彩色图像加密

Multiple-color-image compression and encryption by using discrete wavelet transform in Fresnel transform domain
作者单位
四川大学 电子信息学院, 成都 610065
摘要
为了解决多彩色图像加密后, 解密图像质量不佳、数据量大以及传输时速率慢的问题, 采用了一种基于小波变换和菲涅耳变换的多彩色图像加密方法, 加密过程中, 利用小波变换的多级分解特性提取每幅彩色图像的低频分量, 将低频分量分别重组为三元组图像(R, G和B), 并且依次将三元组图像(R, G和B)通过菲涅耳域中的衍射加密系统, 对这3个三元组图像进一步加密, 从而实现了多彩色图像的加密。结果表明, 该方法不仅可以高质量地恢复原始彩色图像, 而且可以同时对4幅彩色图像进行加密, 提高了加密彩色图像的容量; 原始图像经过小波变换,其数据量压缩到原来的1/4, 有利于数据的传输和存储。该算法能够有效地同时对多幅色彩图像进行压缩和加密, 不仅提高了解密图像的质量, 并且具有较高的密钥敏感度和较好的鲁棒性。
Abstract
In order to solve the problems of the low quality of image, the large amount of data and the slow rate of transmission, an optical compression and encryption method of multiple-color images by using discrete wavelet transform in Fresnel transform domain had been proposed. In the process of encryption, the low-frequency components of each color image were extracted by using the multilevel decomposition characteristics of wavelet transform, and the low frequency components were reorganized to triplet images (R, G and B),respectively. And the triplet images (R, G and B) were sequentially encrypted through the diffraction encryption system in the Fresnel domain. After triplet images were further encrypted, the encryption of multi-color images was realized. The results show that, the method can not only reconstruct the original color image with high quality, but also encrypt 4 color-images at the same time, which increases the capacity of the encrypted color image. The data volume of the encryption is compressed 1/4 after wavelet transform, which is beneficial to the transmission and storage of the data. The algorithm can effectively compress and encrypt multiple-color images at the same time. It not only improves the quality of the decrypted image, but also has high key sensitivity and good robustness.

曾健清, 王君, 陈叶, 刘琦. 小波变换和菲涅耳变换的多彩色图像加密[J]. 激光技术, 2018, 42(6): 733. ZENG Jianqing, WANG Jun, CHEN Ye, LIU Qi. Multiple-color-image compression and encryption by using discrete wavelet transform in Fresnel transform domain[J]. Laser Technology, 2018, 42(6): 733.

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