Generalized Wiener reconstruction of images from colour sensor data using a scale invariant prior

D. Taubman
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引用次数: 60

Abstract

An algorithm is described for reconstructing images from colour sensor samples, which need not be aligned nor conform to a rectangular sampling geometry. The algorithm has applications in de-mosaicing digital camera color filter array (CFA) data, and processing other imaging modalities such as scanned images and captured video. A unique scale invariant WSS prior model is described for the uncorrupted surface spectral reflectance functions and used to form linear least mean squared error (LLMSE) optimal reconstructions with constrained support operators. Some important results are established concerning the existence and tractability of the solutions based on this prior.
利用尺度不变先验对颜色传感器数据进行广义维纳重构
描述了一种用于从颜色传感器样本重建图像的算法,该算法不需要对齐也不符合矩形采样几何。该算法可用于数字相机彩色滤波阵列(CFA)数据的去拼接,以及扫描图像和捕获视频等其他成像方式的处理。针对未损坏的表面光谱反射函数,提出了一种独特的尺度不变WSS先验模型,并利用该模型建立了具有约束支持算子的线性最小均方误差(LLMSE)最优重构。在此基础上,得到了一些重要的结果,证明了解的存在性和可追溯性。
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