文章基本信息

标题：Demosaicing of Real Low Lighting Images using CFA 3.0
本地全文：下载
作者：Chiman Kwan ; Jude Larkin ; Bence Budavari 等
期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2020
卷号：11
期号：4
页码：25-41
DOI：10.5121/sipij.2020.11403
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In CFA 2.0, there are white pixels in a color filter array (CFA) that has proven to help the demosaicing performance for images collected in low light conditions. Here, we evaluate the performance of demosaicing for images collected in low light conditions using an RGBW pattern with 75% white pixels. We term this CFA the CFA 3.0. Using a data set containing 10 images collected in low light conditions, we performed extensive experiments. Both objective and subjective evaluations were used in our experiments.
关键词：Debayering;demosaicing;color filter array (CFA);RGBW pattern;Bayer pattern;CFA 1.0;CFA2.0;CFA3.0;pansharpening;deep learning