SPARSITY BASED POISSON INPAINTING

被引：0

作者：

Giryes, Raja ^{[1
]}

Elad, Michael ^{[1
]}

机构：

[1] Technion Israel Inst Technol, Dept Comp Sci, IL-32000 Haifa, Israel

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2014年

关键词：

Sparse Approximation; Poisson Denoising; Inpainting; Dictionary Learning; Greedy Methods;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Poisson noise appears in various imaging applications, such as low-light photography, medical imaging and space imaging. In many cases we may have occlusions in the received image in addition to the noise. Thus, the problem of Poisson denoising turns to be a Poisson inpainting one in which we need both to remove the noise and recover the values in the occluded locations. In this work we extend a recent novel Poisson denoising method for the task of image inpainting. To the best of our knowledge this is the first work that deals with the problem of Poisson inpainting.

引用

页码：2839 / 2843

页数：5

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