Generic Demosaicking Method for Multispectral Filter Arrays Based on Adaptive Frequency Domain Filtering

Zechen Wang, Geng Zhang, Bing-liang Hu
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Abstract

Multispectral filter arrays (MSFAs) are widely applied to achieve snapshot multispectral imaging on a single image sensor, which causes incomplete data of each channel in the original captured image, and thus a process of estimating missing data named “demosaicking” is needed for high spatial resolution imaging. In a multispectral imaging system equipped with MSFA, as the number of spectral channels increases, the lack of data in the original captured image becomes severer, which brings great challenges to the demosaicking process, and thus classical demosaicking methods for MSFAs often fail to satisfy both reconstructed image quality and computational efficiency. In this paper, we propose a generic demosaicking method for MSFAs based on adaptive frequency domain filtering (AFDF) which achieves high quality of reconstructed images with little computational cost. Experimental results demonstrate that our proposed demosaicking method outperforms the state-of-the-art methods in terms of both quality of reconstructed images and processing time.
基于自适应频域滤波的多谱滤波阵列通用去马赛克方法
多光谱滤波阵列(MSFAs)被广泛应用于在单个图像传感器上实现快照多光谱成像,导致原始捕获图像中各通道数据不完整,因此需要对缺失数据进行估计,称为“去马赛克”,以实现高空间分辨率成像。在配备MSFA的多光谱成像系统中,随着光谱通道数量的增加,原始捕获图像的数据缺失变得更加严重,这给去马赛克过程带来了很大的挑战,传统的MSFA去马赛克方法往往无法满足重建图像质量和计算效率的要求。本文提出了一种基于自适应频域滤波(AFDF)的msfa通用去马赛克方法,以较少的计算成本获得高质量的重建图像。实验结果表明,我们提出的去马赛克方法在重建图像的质量和处理时间方面都优于目前最先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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