Robust color demosaicking via vectorial hessian frobenius norm regularization

Xuan Wu, Songze Tang, Lili Huang, W. Shao, Pengfei Liu, Zhihui Wei
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引用次数: 1

Abstract

Single sensor camera captures scenes using a color filter array, such that each pixel samples only one of the three primary colors. A process called color demosaicking (CDM) is used to produce full color image. In this paper, we present a new variational model for high quality CDM. The robust data term is measured by Z1-norm to repress the heavy tailed artifacts. The regularization term is measured by vectorial Hessian Frobenius norm (VHFN) to capture the higher order edges as well as the intra-correlations across different channels simultaneously. To solve the proposed model, an efficient algorithm is designed using alternating direction method of multiplier (ADMM). Experimental results demonstrate that the proposed CDM method outperforms many state-of-the-art methods in reducing color artifacts, preserving the sharp edges and reconstructing fine details.
通过向量hessian frobenius范数正则化实现鲁棒色彩去马赛克
单传感器相机使用彩色滤光片阵列捕捉场景,这样每个像素只采样三种原色中的一种。一种称为彩色去马赛克(CDM)的工艺被用来产生全彩色图像。本文提出了一种新的高质量CDM变分模型。鲁棒数据项采用z1范数测量,以抑制重尾伪影。通过向量Hessian Frobenius范数(VHFN)测量正则化项,同时捕获高阶边和不同信道间的内相关性。为了求解该模型,设计了一种高效的乘法器交替方向法。实验结果表明,该方法在减少彩色伪影、保留锐利边缘和重建精细细节方面优于许多现有的方法。
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