• Laser & Optoelectronics Progress
  • Vol. 57, Issue 8, 081003 (2020)
Tingting Liu1, Yujin Zhang1、2、*, Fei Wu1, and Shiting Xiong1
Author Affiliations
  • 1School of Electrical and Electronic Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
  • 2Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai Jiao Tong University, Shanghai 200240, China
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    DOI: 10.3788/LOP57.081003 Cite this Article Set citation alerts
    Tingting Liu, Yujin Zhang, Fei Wu, Shiting Xiong. Diffusion-Based Image Inpainting Forensics Via Gradient Domain Guided Filtering Enhancement[J]. Laser & Optoelectronics Progress, 2020, 57(8): 081003 Copy Citation Text show less

    Abstract

    Diffusion-based inpainting is a common method of small-area image tampering, considering the blurring effect introduced by diffusion-based image inpainting, this paper proposes a method of diffusion-based image inpainting forensics via gradient domain guided filtering enhancement. Since the texture of the forged image is clear in the untouched regions, and the blurring effect results in some texture changes in the inpainted regions, gradient domain guided filtering can better preserve the texture structure of the untouched regions and highlight the blurring effect of the inpainted regions. In view of the fact that the tampered information is reflected to different extend in different color channels, the gradient domain guided filtering is applied to enhance each color channel of the input image, which captures the impact of image inpainting from multiple perspectives. Experimental results show that this method can not only detect and locate the diffusion-based image inpainting regions effectively, but also has better detection performance than the existing methods.
    Tingting Liu, Yujin Zhang, Fei Wu, Shiting Xiong. Diffusion-Based Image Inpainting Forensics Via Gradient Domain Guided Filtering Enhancement[J]. Laser & Optoelectronics Progress, 2020, 57(8): 081003
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