Image Inpainting Based on Adaptive Total Variation Model

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概要

• 論文の詳細を見る

• In this letter, a novel adaptive total variation (ATV) model is proposed for image inpainting. The classical TV model is a partial differential equation (PDE)-based technique. While the TV model can preserve the image edges well, it has some drawbacks, such as staircase effect in the inpainted image and slow convergence rate. By analyzing the diffusion mechanism of TV model and introducing a new edge detection operator named difference curvature, we propose a novel ATV inpainting model. The proposed ATV model can diffuse the image information smoothly and quickly, namely, this model not only eliminates the staircase effect but also accelerates the convergence rate. Experimental results demonstrate the effectiveness of the proposed scheme.

• 2011-07-01

著者

• LI Leida

  School of Information and Electrical Engineering, China University of Mining and Technology

• Lu Zhaolin

  School Of Computer Science And Technology China University Of Mining And Technology

• Li Leida

  School Of Information And Electrical Engineering China University Of Mining And Technology

• QIAN Jiansheng

  School of Information and Electrical Engineering, China University of Mining and Technology

• Qian Jiansheng

  School Of Information And Electrical Engineering China University Of Mining And Technology

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• Image Inpainting Based on Adaptive Total Variation Model
• ADAPTIVE TOTAL VARIATION MODEL FOR IMAGE INPAINTING AND DENOISING
• Image Watermarking Based on Invariant Representation of Polar Sine Transform

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