1. Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
2. Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China
3. Geographical Environment Research and Education Center, Capital Normal University, Beijing 100048, China
Abstract:Most of the current research focuses on the improvement and application of spatial and spectral resolution of Hyperspectral Image(HSI). It pays little attention to the comprehensive application of radiation resolution. The radiation resolution reflects the range of the dynamic change of the radiation energy received by the sensor. It detects the small change of the radiation energy of the ground object, which also contains rich ground object information. This study proposes a HSI Radiation Bit Depth Residual Quantization Method to construct Low Bit Depth Hyperspectral Image (LHSI) and Residual Hyperspectral Image (RHSI)with different radiation bit depth levels. Through experiments, LHSI and RHSI of different radiation bit depth levels of HSI and their combinations are used to classify ground objects, and their effects on the classification accuracy of ground objects are analyzed. Experiments show that, based on ensuring a certain classification accuracy, 9-bit LHSI retains the main information of HSI; 4-bit RHSI highlights more details of ground objects than the HSI. The combination of 13-bit LHSI and 3-bit RHSI can not only retain the main information of HSI but also highlight the details of the ground object.
[1] Zhang X,Zhang A,Li M,et al. Sensors,2020,20(16):4589.
[2] GUAN Yuan-xiu,CHENG Xiao-yang(关元秀,程晓阳). Guide to High Resolution Satellite Image Processing(高分辨率卫星影像处理指南). Beijing: Science Press(北京:科学出版社),2008.
[3] JI Lei,ZHANG Xin,ZHANG Li-mei,et al(纪 磊,张 欣,张丽梅, 等). Laser & Optoelectronics Progress(激光与光电子学进展),2020,57(6):165.
[4] Awad M M. Journal of Forestry Research,2018,29(5):1395.
[5] Wang K,Cheng L,Yong B. Remote Sensing,2020,12(13):2154.
[6] Huang H,Duan Y,Shi G,et al. IEEE Access,2018,6:15224.
[7] Chen Z,Jiang J,Zhou C,et al. IEEE Access,2019,7:147796.
[8] Tu B,Zhang X,Kang X,et al. IEEE Geoscience & Remote Sensing Letters,2018,15(3):340.
[9] Thenkabail Prasad S. Remotely Sensed Data Characterization,Classification,and Accuracies. United States Geological Survey (USGS),2015.
[10] Tucker Compton J. International Journal of Remote Sensing,1980,1(3):241.
[11] Franks S,Masek J. How Many Bits? Radiometric Resolution as a Factor in Obtaining Forestry Information With Remotely Sensed Measurements, IGARRS, Barcelona, 2007.
[12] Irons J R,Markham B L,Nelson R F,et al. International Journal of Remote Sensing,1985,6(8):1385.
[13] Tucker C J. International Journal of Remote Sensing,1980,1(3):241.
[14] Rao N R,Garg P K,Ghosh S K. Mapping Sciences & Remote Sensing,2006,43(4):377.
[15] Rama Rao N,Garg P K,Ghosh S K. International Journal of Remote Sensing,2007,28(2):443.
[16] Verde N,MallinSI G,Tsakiri-Strati M,et al. Remote Sensing,2018,10(8):1267.
[17] KANG Xiao-yan,ZHANG Ai-wu(康孝岩,张爱武). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2019,39(10):3013.
[18] ZHANG Ai-wu,ZHANG Tai-pei,KANG Xiao-yan,et al(张爱武,张泰配,康孝岩,等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2018,34(19):7.
[19] Mourya D,Bhatt A. Classification of Hyperspectral Imagery Using Random Forest, International Conference on Next Generation Computing Technologies. Springer,Singapore,2017:66.
[20] YE Zhen,HE Ming-yi(叶 珍,何明一). Journal of Image and Graphics(中国图象图形学报),2015,20(1):8.
[21] Wallace G K. Communications of the ACM,1991,34(4):30.
[22] Belyaev E,Mantel C,Forchhammer S. Proc SPIE,2017,10403:104030A(https://doi.org/10.1117/12.2275542).
[23] Li Z,Ni B,Zhang W,et al. Performance Guaranteed Network Acceleration via High-Order Residual Quantization, Proceedings of the IEEE International Conference on Computer Vision. 2017:2584.
[24] Shrivastava P,Singh U P. Noise Removal Using First Order Neighborhood Mean Filter, 2014 Conference on IT in Business Industry and Government (CSIBIG), 2014, 1.
[25] Okwonu F Z,Asaju B L,Arunaye F I. IOP Conference Series Materials Science and Engineering,2020,917:012065.
[26] Cao C,Yu J,Zhou C,et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2019,(3):973.
[27] Fitzgerald R W,Lees B G. Remote Sensing of Environment,1994,47(3):362.
[28] Xu W N,Wang P X,Han P,et al. Journal of Natural Disasters,2011,20(6):81.
[29] Katiyar S K,Arun P V. IEEE Transactions on Geoscience & Remote Sensing,2014,50(11b):68.