一种基于分块压缩感知的鲁棒图像散列算法

图像散列算法是一种把数字图像映射为一个基于内容的简短二进制比特串的技术，它具有鲁棒性、安全性、紧凑性和单向性等特点，已被广泛应用于图像鉴别与图像识别领域中。本文提出一种基于分块压缩感知的鲁棒图像散列算法，其设计利用了压缩感知采样阶段的计算保密及线性运算的特点。该算 法通过对图像进行分块，利用压缩感知理论在密钥的控制下将图像块随机投影为一个测量值向量序列，并把每个测量值向量量化为一个比特，得到一个长度可由分块策略调整的二进制散列值。实验结果表明，本文算法在鲁棒性、安全性和运算速度等方面具有良好的性能。

Robust Image Hashing Based on Block Compressed Sensing

Image hashing is a technique to map a digital image into a content-based and short binary code. It has the properties of robustness, security, compactness and one-wayness, which has been widely applied in the field of image authentication and identification. Here, a robust image hashing algorithm based on block compressed sensing is proposed, using the characteristics of secure computation and linear operation in the sampling stage. In the proposed algorithm, the input image is partitioned into sub-blocks. For each sub-block, random projection is applied to it based on the theory of compressed sensing, and a measurement vector can be obtained under the control of the secret key. Then each measurement vector is quantized as one bit and finally a binary hash value can be obtained whose length can be adjusted by the strategy of image partition. Experimental results show that the proposed algorithm has satisfied performance in robustness, security and speed.