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Volume: 28 | Article ID: art00012
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A Learning-based Approach to Image Demosaicking with Spatial Autocorrelation Analysis
  DOI :  10.2352/ISSN.2470-1173.2016.20.COLOR-314  Published OnlineFebruary 2016
Abstract

We introduce a two stage image demosaicking method for Bayer color filter array (CFA) images. Pixel interpolation using a Bayesian and/or SVM classifier is followed by renegotiation of the interpolated image with an auto-correlation function (ACF), which is applied to the distribution of edge strengths at each pixel of the interpolated image. This second stage can also be used to post-process images produced by other demosaicking methods. Experimental results obtained with the Kodak PhotoCD benchmark show that our method shows enhanced edge and texture details and when compared with three other methods

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Min-Kook Choi, Chan Joo, Hyun-Gyu Lee, Sang-Chul Lee, "A Learning-based Approach to Image Demosaicking with Spatial Autocorrelation Analysisin Proc. IS&T Int’l. Symp. on Electronic Imaging: Color Imaging XXI: Displaying, Processing, Hardcopy, and Applications,  2016,  https://doi.org/10.2352/ISSN.2470-1173.2016.20.COLOR-314

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Copyright © Society for Imaging Science and Technology 2016
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Electronic Imaging
2470-1173
Society for Imaging Science and Technology