Color demosaicking with the spatial alignment property of spectral Laplacians

Danhua Liu, Yufei Guo, Dahua Gao, Xueyan Song, Guangming Shi
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Abstract

We present a color demosaicking method which aims to improve the demosaicking performance by thoroughly exploiting domain knowledge to confine the solution space for the underlying true color image. We use a physically-induced model to infer spatial alignment property of spectral Laplacians. Specifically, the 2D Laplacians of different channels are sparse, and it benefits spatial alignment property across different color channels. Then, we establish an optimization model, using the image formation model and the spatial alignment property of spectral Laplacians, to solve the ill-posed problem of the color demosaicking. Finally, some extensive experiments have been done and show the availability of our approach in color image demosaicking.
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利用光谱拉普拉斯算子空间对准特性的彩色去马赛克
本文提出了一种彩色去马赛克方法,该方法通过充分利用领域知识来限制底层真彩色图像的解空间,从而提高去马赛克性能。我们使用物理诱导模型来推断光谱拉普拉斯子的空间排列特性。具体来说,不同通道的二维拉普拉斯向量是稀疏的,这有利于不同颜色通道的空间对齐特性。然后,利用图像形成模型和光谱拉普拉斯算子的空间对准特性,建立优化模型,解决彩色去马赛克的不适定问题。最后,进行了大量的实验,证明了该方法在彩色图像去马赛克中的有效性。
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