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Identifying source camera using guided image estimation and block weighted average

机译:使用引导图像估计和块加权平均值识别源摄像机

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Sensor pattern noise (SPN) has been widely used in source camera identification. However, the SPN extracted from natural image may be contaminated by its content and eventually introduce side effect to the identification accuracy. In this paper, an effective source camera identification scheme based on guided image estimation and block weighted average is proposed. Before the SPN extraction, an adaptive SPN estimator based on image content is implemented to reduce the influence of image scene and improve the quality of the SPN. Furthermore, a novel camera reference SPN construction method is put forward by using some ordinary images, instead of the blue sky images in the previous schemes, and a block weighted average approach is used to suppress the influence of the image scenes in the reference SPN. Experimental results and analysis indicate that the proposed method can effectively identify the source of the natural image, especially in actual forensics environment with a small number of images. (C) 2016 Elsevier Inc. All rights reserved.
机译:传感器模式噪声(SPN)已广泛用于源摄像机识别。但是,从自然图像中提取的SPN可能会被其内容污染,并最终给识别精度带来副作用。提出了一种基于导引图像估计和块加权平均的有效源摄像机识别方案。在提取SPN之前,要实现基于图像内容的自适应SPN估计器,以减少图像场景的影响并提高SPN的质量。此外,提出了一种通过使用一些普通图像代替以前方案中的蓝天图像的新型摄像机参考SPN构造方法,并采用块加权平均的方法来抑制参考SPN中图像场景的影响。实验结果和分析表明,该方法可以有效地识别自然图像的来源,特别是在少量图像的实际取证环境中。 (C)2016 Elsevier Inc.保留所有权利。

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