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Least Square Based approach for Image Inpainting

Publication Type : Journal Article

Publisher : Institute of Integrative Omics and Applied Biotechnology

Source : Institute of Integrative Omics and Applied Biotechnology, Volume 7, p.44-59 (2016)

Url : http://www.iioab.org/IIOABJ_7(3)/IIOABJ_7(3)44-59.pdf

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking, Electronics Communication and Instrumentation Forum (ECIF)

Department : Center for Computational Engineering and Networking (CEN), Electronics and Communication

Year : 2016

Abstract : Images are widely used over various applications under the aegis of various domains like Computer vision, Biomedical, etc. The problem of missing data identification is of great concern in various fields involving image processing. Least square can be used for missing sample estimation for 1-D signals. The proposed system extends the missing sample estimation in 1-D using least square to 2-D, applied for image inpainting. The paper also draws a comparison between the Total Variation (TV) algorithm and the proposed method. The experiments were conducted on standard images and the standard metrics namely PSNR and SSIM are used to compare the image quality obtained using the proposed method (least square based) and TV algorithm.

Cite this Research Publication : A. M, N, D., Sowmya, Mahan, D. Neethu, and Dr. Soman K. P., “Least Square Based approach for Image Inpainting”, Institute of Integrative Omics and Applied Biotechnology, vol. 7, pp. 44-59, 2016.

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