返回
Fast model-based multispectral imaging using nonnegative principal component analysis
DOI:10.1364/OL.37.001937.png)
摘要
En 中文
Estimation of the spectral reflectance of a scene is a critical problem in image processing and computer vision applications. Model-based multispectral imaging, one of the spectral reflectance estimation methods, can effectively reconstruct the full spectrum using a small number of camera shots. However, it is based on iterative optimization and, thus, is computationally too intensive. In this Letter, we modify the iterative optimization problem to a closed-form problem using nonnegative principal component analysis. The proposed method can substantially reduce the computational cost while maintaining the accuracy. (C) 2012 Optical Society of America
Keyword:
SPECTRAL REFLECTANCE
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
4.0W
被引数:
7.6W
机构
引用论文
Snapshot Image Mapping Spectrometer (IMS) with high sampling density for hyperspectral microscopy
OPTICS EXPRESS
IF3.3

