基于二次模糊相关性的单通道置换图像盲分离

Blind Separation of Single Channel Permuted Image Based on Double Blur Correlation

针对模糊处理后的置换图像,提出一种基于二次模糊相关性的单通道盲分离方法.该方法通过对置换图像进行二次模糊,估计二次模糊前后对应子块的相关系数来构造一个映射空间,利用映射空间内参数的不同分类完成置换混合矩阵的估计,从而实现置换源图像子块的分离.实验表明,该方法对经历不同模糊处理的置换图像均能达到较高的检测正确率,同时,算法对高斯噪声和有损JPEG压缩都具有较好的鲁棒性.

This paper proposes a single-channel blind separation scheme using double blur correlation for blurring permuted images. The permuted image is blurred again and the correlation coefficients of image blocks are estimated before and after double blurring. Using the estimated correlation coefficients, a mapping space is constructed. The permutation mixing matrixes can be accurately estimated by classifying the parameters in the mapping space, thus the source images can be separated. Simulation results show high detection accuracy for permuted images with various blurring operations. The proposed method has good robustness against Gaussian noise and lossy JPEG compression.