Daylight Spectrum Estimation from Hyper-and Multispectral Image without Area Extraction of Uniform Materials

Eiji Kaneko, H. Aoki, M. Tsukada
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引用次数: 1

Abstract

This paper presents a method for estimating daylight spectrum accurately from a hyperspectral (HS)/multispectral (MS) image without area extraction of uniform materials. To identify materials from spectra obtained with an HS/MS camera in outdoor environments, the daylight spectrum in the scene needs to be estimated and removed. A major conventional method for estimating an illumination spectrum based on the dichromatic reflection model requires extracting multiple areas each covering a highlighted uniform material from images beforehand. The proposed method employs a daylight spectrum model and estimates the daylight spectrum as a point within a model subspace in the spectral space, which minimizes the distance from the hyper-plane on which observed spectra distribute. Experimental results with images of rippled water surface show that the proposed method successfully estimates daylight spectrum without the area extraction. The estimation error of the proposed method evaluated with spectral angle mapper is 2.75° on average, which is almost equivalent to the intrinsic error of the daylight model itself, whereas that of the conventional method is 6.83°.
无均匀材料区域提取的高光谱和多光谱图像日光光谱估计
本文提出了一种不需要对均匀材料进行区域提取,就能从高光谱(HS)/多光谱(MS)图像中准确估计日光光谱的方法。为了从室外环境中HS/MS相机获得的光谱中识别材料,需要对场景中的日光光谱进行估计和去除。一种基于二色反射模型估计照明光谱的主要传统方法需要事先从图像中提取多个区域,每个区域覆盖一个高亮的均匀材料。该方法采用日光光谱模型,将日光光谱估计为光谱空间中模型子空间中的一个点,从而使观测光谱分布的超平面距离最小。对波纹水面图像的实验结果表明,该方法在不提取区域的情况下成功地估计了日光光谱。利用光谱角成像仪估算该方法的估计误差平均为2.75°,与日光模型本身的固有误差基本相当,而传统方法的估计误差为6.83°。
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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