光谱学与光谱分析 |
|
|
|
|
|
A New Spectral Similarity Measure Based on Multiple Features Integration |
KONG Xiang-bing1, SHU Ning1, TAO Jian-bin2, GONG Yan1 |
1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China 2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China |
|
|
Abstract Spectral characterization and feature selection is the key to spectral similarity measure which is the basis of both quantitative analysis and accurate object identification for hyperspectral remote sensing. However, spectral similarity measures using only one spectral feature are usually ambiguous in their distinction of similarity. Multiple spectral features integration is needed for objective spectral discrimination. We present a new spectral similarity measure, Spectral Pan-similarity Measure (SPM), based on geometric distance, correlation coefficient and relative entropy. Spectral Pan-similarity Measure objectively quantifies differences between spectra in three spectral features, the vector magnitude, spectral curve shape and spectral information content. The performance of different spectral similarity measures is compared using USGS Mineral Spectral Library and real (i.e., Operational Modular Imaging Spectrometer, OMIS) hyperspectral image. The experimental results demonstrate that the new spectral similarity measure is more effective than the spectral similarity measure taking into account only one or two features both in spectral discriminatory power and spectral identification uncertainty.
|
Received: 2010-10-11
Accepted: 2011-04-11
|
|
Corresponding Authors:
KONG Xiang-bing
E-mail: kongxb_whu@foxmail.com,kong.xb@hotmail.com
|
|
[1] TONG Qing-xi, ZHANG Bing, ZHENG Lan-fen(童庆禧, 张 兵, 郑兰芬). Hyperspectral Remote Sensing: Principle, Technology and Application(高光谱遥感——原理、技术与应用). Beijing: Higher Education Press(北京: 高等教育出版社), 2006. 40. [2] DU Pei-jun, TANG Hong, FANG Tao(杜培军, 唐 宏, 方 涛). Geomatics and Information Science of Wuhan University(武汉大学学报·信息科学版), 2006, (2): 112. [3] Chang C I, Chakravarty S, Chen H M, et al. Pattern Recognition, 2009, 42(3): 395. [4] Keshava N. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(7): 1552. [5] Kruse F A, Lefkoff A B, Boardman J W, et al. Remote Sensing Environment, 1993, 44(2-3): 145. [6] Sohn Youngsinn, Rebello N Sanjay. Photogrammetric Engineering and Remote Sensing, 2002, 68(12): 1271. [7] Vander Meer F, Bakker W. Int. J. Remote Sensing, 1997, 18(5): 1197. [8] Chang C I. IEEE Transactions on Information Theory, 2000, 46(5): 1927. [9] Chang C I. Hyperspectral Imaging: Techniques for Spectral Detection and Classification. Dordrecht:Kluwer Academic Publishers, 2003. 15. [10] Van der Meer F. International Journal of Applied Earth Observation and Geoinformation,2006, 8(1): 3. [11] Sweet J N. IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, 2003,27-28: 92. [12] FANG Sheng-hui, GONG Hao(方圣辉, 龚 浩). Geomatics and Information Science of Wuhan University(武汉大学学报·信息科学版), 2006, 31(12): 1044. [13] Du Y, Chang C I, Ren H. Optical Engineering, 2004, 43(8): 1777. [14] Granahan J C, Sweet J N. IEEE 2001 International Geoscience and Remote Sensing Symposium, 2001,(5): 2022. [15] Duda R O, Hart P E,Stork D G. Pattern Classification(2nd ed.). New York: John Wiley and Sons, 2001, (Chapter 4): 31. [16] Clark R N, Swayze G A, Gallagher A J, et al. The US Geological Survey, Digital Spectral Library: Version 1: 0.2 to 3. 0 microns, US Geological Survey Open File Report 93-592, 1993: 1340.
|
[1] |
ZHU Wen-jing1, 2,FENG Zhan-kang1, 2,DAI Shi-yuan1, 2,ZHANG Ping-ping3,JI Wen4,WANG Ai-chen1, 2,WEI Xin-hua1, 2*. Multi-Feature Fusion Detection of Wheat Lodging Information Based on UAV Multispectral Images[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 197-206. |
[2] |
YANG Sen1, ZHANG Xin-ao1, XING Jian1, DAI Jing-min2. Study on Multi-Feature Model Fusion Variety Classification and Multi-Parameter Appearance Inspection for Milled Rice[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2837-2842. |
[3] |
YE Wen-chao1, LUO Shui-yang1, LI Jin-hao1, LI Zhao-rong1, FAN Zhi-wen1, XU Hai-tao1, ZHAO Jing1, LAN Yu-bin1, 2, DENG Hai-dong1*, LONG Yong-bing1, 2, 3*. Research on Classification Method of Hybrid Rice Seeds Based on the Fusion of Near-Infrared Spectra and Images[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2935-2941. |
[4] |
FENG Hai-kuan1, 2, YUE Ji-bo3, FAN Yi-guang2, YANG Gui-jun2, ZHAO Chun-jiang1, 2*. Estimation of Potato Above-Ground Biomass Based on VGC-AGB Model and Hyperspectral Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2876-2884. |
[5] |
JIN Chun-bai1, YANG Guang1*, LU Shan2*, LIU Wen-jing1, LI De-jun1, ZHENG Nan1. Band Selection Method Based on Target Saliency Analysis in Spatial Domain[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2952-2959. |
[6] |
GAO Yu1, SUN Xue-jian1*, LI Guang-hua2, ZHANG Li-fu1, QU Liang2, ZHANG Dong-hui1, CHANG Jing-jing2, DAI Xiao-ai3. Study on the Derivation of Paper Viscosity Spectral Index Based on Spectral Information Expansion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2960-2966. |
[7] |
KONG Bo1, YU Huan2*, SONG Wu-jie2, 3, HOU Yu-ting2, XIANG Qing2. Hyperspectral Characteristics and Quantitative Remote Sensing Inversion of Gravel Grain Size in the North Tibetan Plateau[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2381-2390. |
[8] |
ZHANG Zhi-fen1, LIU Zi-min1, QIN Rui1, LI Geng1, WEN Guang-rui1, HE Wei-feng2. Real-Time Detection of Protective Coating Damage During Laser Shock Peening Based on ReliefF Feature Weight Fusion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2437-2445. |
[9] |
YANG Dong-feng1, HU Jun2*. Accurate Identification of Maize Varieties Based on Feature Fusion of Near Infrared Spectrum and Image[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2588-2595. |
[10] |
ZHANG Xia1, WANG Wei-hao1, 2*, SUN Wei-chao1, DING Song-tao1, 2, WANG Yi-bo1, 2. Soil Zn Content Inversion by Hyperspectral Remote Sensing Data and Considering Soil Types[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2019-2026. |
[11] |
WANG Hui-min1, 2, YU Lei1, XU Kai-lei1, 2, JIANG Xiao-guang1, 2, WAN Yu-qing1, 2*. Estimation of Salt Content of Saline Soil in Arid Areas Based on GF-5 Hyperspectral Image[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2278-2286. |
[12] |
CAO Yang1, 2, LI Yan-hong1, 2*. Study on the Effects of NO2 Pollution Under COVID-19 Epidemic
Prevention and Control in Urumqi[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1981-1987. |
[13] |
ZHONG Jing-jing1, 2, LIU Xiao1, 3, WANG Xue-ji1, 3, LIU Jia-cheng1, 3, LIU Hong1, 3, QI Chen1, 3, LIU Yu-yang1, 2, 3, YU Tao1, 3*. A Multidimensional Information Fusion Algorithm for Polarization
Spectrum Reconstruction Based on Nonsubsampled Contourlet
Transform[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1254-1261. |
[14] |
ZHANG Chao1*, SU Xiao-yu1, XIA Tian2, YANG Ke-ming3, FENG Fei-sheng4. Monitoring the Degree of Pollution in Different Varieties of Maize Under Copper and Lead Stress[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1268-1274. |
[15] |
XU Long-xin1, 2, 3, 4, SUN Yong-hua2, 3, 4*, WU Wen-huan1, ZOU Kai2, 3, 4, HE Shi-jun2, 3, 4, ZHAO Yuan-ming2, 3, 4, YE Miao2, 3, 4, ZHANG Xiao-han2, 3, 4. Research on Classification of Construction Waste Based on UAV Hyperspectral Image[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3927-3934. |
|
|
|
|