Earticle

초록

영어

Image inpainting is an important research topic in the field of image processing. The goal of inpainting is to recover the lost information of the target region from the rest of the image. Inpainting techniques can be applied in areas such as old photo restoration, object removal and demosaicing. Based on previous literatures of image inpainting and image modeling, we categorize inpainting processes of different methods and algorithms into the structure layer and the texture layer. Then the mathematical inpainting models and the formations of image impairment are analyzed and evaluated in detail. Experimental results are provided in the fifth section regarding to eight different algorithms measured by Peak Signal to Noise Ratio (PSNR) as well as direct visual perception.

목차

Abstract
 1. Introduction
 2. Structure
  2.1. Partial Differential Equations Methods
  2.2. Exemplar Based Methods
 3. Texture
 4. Sparse Inpainting
  4.1. Sparse Compression
  4.2. Computing the Sparse Representation Matrix
  4.3. Dictionary
  4.4. Sparse-Representation-Based Inpainting
 5. Experiment
 6. Conclusion
 References

키워드

저자

• Chang Shu [ University of Electronic Science and Technology of China, Chengdu, China ]
• Yaojie Liu [ The Ohio State University, Columbus, USA ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605