Application of residue number system (RNS) to image processing using orthogonal transformation

G. Armah, Emmanuel Ahene
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引用次数: 4

Abstract

Several techniques for image encryption have been proposed over the years with significant consideration of basic cryptographic goals such as authentication, integrity and confidentiality. Recently, another method for encrypting image data using an Orthogonal transform namely Walsh Hadamard transform on residual number system have been proposed. In this paper, we basically analyse this approach and propose an efficient method for this type of encryption scheme. We modify the transform algorithm of the previous technique by implementing the Fast Walsh Hadamard transform algorithm. The fast Walsh Hadamard transform algorithm has been proved to be the efficient algorithm to compute the Walsh Hadamard transform with computational complexity of O(N log N). We emphasise that the naive implementation of the Walsh Hadamard transform yields a computational complexity of O(N2). In this paper we demonstrate the efficiency of our approach using 32 chosen eigenvalues in the key generation algorithm. The eigenvalues are derived from a reference image. Throughout the processes on the image data, we use modular arithmetic to ensure that computations with the resulting RNS become very efficient. Moreover, the approach considers image in a divided matrix domain and finally combines all independent cryptographic operations as encryption is a one-to-one mapping. This deals with the possibility of having any pixel value ill-stored or wrongly received at the receiver end, without affecting the decryption process. However, the final recovered image will differ by a negligible amount.
残数系统在正交变换图像处理中的应用
多年来,人们提出了几种图像加密技术,并充分考虑了身份验证、完整性和机密性等基本密码学目标。近年来,提出了另一种利用正交变换对图像数据进行加密的方法,即残差数系统上的Walsh Hadamard变换。本文对这种方法进行了基本分析,并提出了一种有效的加密方案。我们通过实现快速Walsh Hadamard变换算法来改进先前技术的变换算法。快速Walsh Hadamard变换算法已被证明是计算Walsh Hadamard变换的有效算法,其计算复杂度为O(N log N)。我们强调,Walsh Hadamard变换的初始实现产生的计算复杂度为O(N2)。在本文中,我们在密钥生成算法中使用32个选择的特征值来证明我们的方法的效率。特征值是从参考图像导出的。在整个图像数据处理过程中,我们使用模块化算法来确保使用所得RNS的计算变得非常高效。此外,该方法考虑图像在分割矩阵域中,最后将所有独立的加密操作组合在一起,因为加密是一对一的映射。在不影响解密过程的情况下,这处理了在接收端错误存储或错误接收任何像素值的可能性。然而,最终恢复的图像会有一个可以忽略不计的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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