Optimized clustering method for spectral reflectance recovery

被引:5
|
作者
Xiong, Yifan [1 ]
Wu, Guangyuan [1 ]
Li, Xiaozhou [2 ]
Wang, Xin [1 ]
机构
[1] Qilu Univ Technol, Shandong Acad Sci, Fac Light Ind, Jinan, Peoples R China
[2] Qilu Univ Technol, Shandong Acad Sci, State Key Lab Biobased Mat & Green Papermaking, Jinan, Peoples R China
来源
FRONTIERS IN PSYCHOLOGY | 2022年 / 13卷
关键词
spectral recovery; dynamic partitional clustering; color space; camera responses; spectral reflectance; RECONSTRUCTION; IMAGE;
D O I
10.3389/fpsyg.2022.1051286
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
An optimized method based on dynamic partitional clustering was proposed for the recovery of spectral reflectance from camera response values. The proposed method produced dynamic clustering subspaces using a combination of dynamic and static clustering, which determined each testing sample as a priori clustering center to obtain the clustering subspace by competition. The Euclidean distance weighted and polynomial expansion models in the clustering subspace were adaptively applied to improve the accuracy of spectral recovery. The experimental results demonstrated that the proposed method outperformed existing methods in spectral and colorimetric accuracy and presented the effectiveness and robustness of spectral recovery accuracy under different color spaces.
引用
收藏
页数:13
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