基于三方加权稀疏编码模型的PRNU提取算法

doi:10.3969/j.issn.0255-8297.2019.05.011

Abstract

Abstract: Estimating the real noise of real-world image is the most important issue of image source forensics based on photo-response non-uniformity (PRNU). Compared with the estimation of additive white Gaussian noise (AWGN), most exsiting noise estimation algorithms used in PRNU extraction behave with poor satisfaction in estimating real noise. In this paper, we propose a PRNU extraction algorithm based on trilateral weighted sparse coding model (TWSCM). TWSCM has advantage in estimating the real noise of real-world image, because it can keep more PRNU noise in the estimation results. Having been tested on the largest image source forensics database, the proposed TWSCM-based PRNU extraction algorithm outperforms the existing algorithm of source forensic.

Key words: image source forensic, photo-response non-uniformity (PRNU), real-word image denoising

CLC Number:

TP391

ZHANG Yongsheng, TIAN Huawei, XIAO Yanhui, HAO Xinze, ZHANG Mingwang. PRNU Extraction Algorithm Based on Trilateral Weighted Sparse Coding Model[J]. Journal of Applied Sciences, 2019, 37(5): 704-710.

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https://www.jas.shu.edu.cn/EN/Y2019/V37/I5/704

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PRNU Extraction Algorithm Based on Trilateral Weighted Sparse Coding Model

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