A Parallel SRM Feature Extraction Algorithm for Steganalysis Based on GPU Architecture

Based on GPU parallel technology, this paper proposes a parallel SRM feature extraction algorithm to accelerate the extraction of SRM feature for steganalysis of HUGO images. Using the parallel program framework of OpenCL for GPU, we parallelize and implement a serial algorithm and employ some optimization technologies for our parallel program to accelerate the extraction process. The techniques include convolution unrolling, combined memory access, aversion of bank conflicts. The experimental results show that the speed of the proposed parallel extraction algorithm for different size images is 25~55 times faster than the original serial algorithm, and 2~4.2 times faster than running the parallel method on Quad-core CPU.