Improved Robust Algorithm for Exemplar based Image Inpainting
TL;DR: An improved robust algorithm for exemplar based inpainting method by modifying the distance function is presented, which proved to be effective in removing large objects from an image, ensuring accurate propagation of linear structures, and eliminating the drawback of "garbage growing" which is a common problem in other methods.
read more
Abstract: Inpainting is technique in which mainly used to filling the region which are damaged and want to recover from unwanted object by collecting the information from the neighbouring pixels. Image inpainting technique has been widely used for reconstructing damaged old photographs and removing unwanted objects from images. In this paper, we present an improved robust algorithm for exemplar based inpainting method by modifying the distance function. The method proved to be effective in removing large objects from an image, ensuring accurate propagation of linear structures, and eliminating the drawback of "garbage growing" which is a common problem in other methods. Experimental results show that our method improves the quality of image inpainting compared with the conventional exemplar-based image completion algorithms. KeywordsTexture Synthesis, Inpainting, PDE, image gradient etc.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Forecasting innovative start-ups through automatic variable selection and MIDAS regressions
TL;DR: This study develops a novel machine learning algorithm to forecast innovative start-ups in Italy, using macroeconomic and financial indicators, and mixed data sampling models, with principal component analysis to reduce regressors and improve estimability.
References
Region filling and object removal by exemplar-based image inpainting
TL;DR: The simultaneous propagation of texture and structure information is achieved by a single, efficient algorithm that combines the advantages of two approaches: exemplar-based texture synthesis and block-based sampling process.
Texture synthesis by non-parametric sampling
Alexei A. Efros,Thomas Leung +1 more
- 20 Sep 1999
TL;DR: A non-parametric method for texture synthesis that aims at preserving as much local structure as possible and produces good results for a wide variety of synthetic and real-world textures.
Pyramid-based texture analysis/synthesis
David J. Heeger,James R. Bergen +1 more
- 15 Sep 1995
TL;DR: This paper describes a method for synthesizing images that match the texture appearance of a given digitized sample, based on a model of human texture perception, and has potential to be a practically useful tool for graphics applications.
Simultaneous structure and texture image inpainting
TL;DR: The novel contribution of this paper is the combination of these three previously developed components, image decomposition with inpainting and texture synthesis, which permits the simultaneous use of filling-in algorithms that are suited for different image characteristics.
Nontexture Inpainting by Curvature-Driven Diffusions
Tony F. Chan,Jianhong Shen +1 more
TL;DR: This third-order PDE model improves the second-order total variation inpainting model introduced earlier by Chan and Shen and is guided by the connectivity principle of human visual perception.
1K