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Research on BAYER Color Filter Array Interpolation Algorithm Based on Sparse Representation

Author: DingLiZuo
Tutor: LianQiuSheng
School: Yanshan University
Course: Circuits and Systems
Keywords: CFA Interpolation Spatial correlation Edge estimated Contourlet transform Local Gaussian Model Color Total Variation PCA denoising Local DCT
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 88
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Abstract


Color CFA interpolation process to reconstruct the full RGB images collected from a single- sensor digital camera images . The single - sensor camera of the color information of the image obtained through the color filter array (CFA) , but the collected images at each pixel location only one of the original color component , in order to recover the other two components to obtain a full-color image , it must be interpolated this process is also called color demosaicking . Learning the existing CFA interpolation algorithm based on the interpolation algorithm used for noiseless and noisy CFA data , complete the following work . First , we use adaptive CFA interpolation algorithm based on the the chromatic aberration channel spatial correlation edge . The interpolation process , the correlation between the RGB channels extending to the chrominance channel , while in order to avoid in the interpolation through the image edge, according to the different regions of the image to estimate the edge orientation directly along the edge direction interpolation . The experiments show that the algorithm can effectively suppress through the pseudo-color edge interpolation . Second , this paper adopts contourlet transform coefficients of image sparse representation , contourlet transform coefficient Laplace distribution as the image a priori knowledge of the local Gaussian model instead of independent , which can effectively transform coefficients o domain statistical characteristics . And while image gradients sparsity binding to image interpolation . Combination of the above points , CFA interpolation algorithm based on the contourlet local Gaussian model with Total Variation . The experiments show that the comparison algorithm with interpolation algorithm in comparative literature , CPSNR values ??and subjective visual effects were significantly increased . Finally , in order to avoid the noisy CFA image interpolation process , introduce noise into the pseudo-color is difficult to remove , this paper first CFA image interpolation before denoising algorithm based on PCA denoising PCA technology to take advantage of the best dimension reduction denoising performance . The CFA image denoising again local DCT transform interpolation . The combination of these two methods , the CFA interpolation algorithm based on PCA space adaptive denoising and local DCT . The experimental results prove that the algorithm can get a better reconstruction of denoising interpolation Noisy CFA image .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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