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Taylor series and adaptive fusion strategy for Bayer demosaicking

机译:泰勒级数和自适应融合策略用于Bayer的去马赛克

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Demosaicking is an important step in generating a full-color image from a color filter array image captured by a single-sensor digital camera. In this paper, we propose a new demosaicking algorithm which uses Taylor series and an adaptive fusion strategy. For generating directional predictors, we present a new interpolator based on Taylor series. The directional predictors are used together with spatial and spectral correlations. Using these predictors and the adaptive fusion strategy improves the green channel interpolation, in turn helping to reconstruct the red and blue channel interpolations. Experiments comparing the proposed algorithm to some other demosaicking algorithms show that the proposed algorithm provides superior performance in terms of both objective and subjective image quality. (C) 2014 Elsevier Inc. All rights reserved.
机译:去马赛克是从单传感器数码相机捕获的滤色镜阵列图像生成全色图像的重要步骤。在本文中,我们提出了一种新的去马赛克算法,该算法使用泰勒级数和自适应融合策略。为了生成方向性预测变量,我们提出了一种基于泰勒级数的新插值器。方向预测变量与空间和频谱相关性一起使用。使用这些预测变量和自适应融合策略可改善绿色通道插值,进而有助于重构红色和蓝色通道插值。通过将所提算法与其他去马赛克算法进行比较的实验表明,所提算法在客观和主观图像质量方面均具有出色的性能。 (C)2014 Elsevier Inc.保留所有权利。

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