为了使图像摘要具有更高的鲁棒性。提出了一种基于视觉特性的图像摘要算法，该算法通过增大人眼敏感的频域系数在计算图像Hash时的权重以使得图像Hash更好地体现视觉特征，并提高鲁棒性。算法首先将原始图像的分块DCT系数乘以若干由密钥控制生成的伪随机矩阵，再对计算的结果进行基于分块的Watson人眼视觉特性处理，最后进行量化判决以产生固定长度的图像Hash序列。实验结果表明，该算法与末采用视觉特性的算法相比，高了对JPEG压缩和高斯漩波的鲁棒性、图像摘要序列由密钥控制生成，因而具有安全性。

An HVS-based image hashing method incorporating a Watson's sensitivity matrix is proposed.The transform domain matrix composed of 8-by-8 block DCT coefficients of the image are multiplied by N matrices that are pseudo-randomly generated with a key,and divided by the periodically extended Watson matrix.By quantization,an N-bit image hash is obtained.Compared to some other hashing methods,the HVS-based hash has better robustness against JPEG compression and low-pass filtering.Since a key is used in the algorithm,the hash is hard to be forged.