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北京航空航天大学 [2]

长春光学精密机械与物... [2]

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	Urban Spatial Resolution Optical Spectral Technology of Scanning Probe Microscope 期刊论文 ACTA MICROSCOPICA, 2019, 卷号: 28, 期号: 6, 页码: 1516-1524 作者: Chen, Guobin; Zheng, Dateng; Zhang, Laigang; Xu, Xiaoxiang 收藏 \| 浏览/下载：14/0 \| 提交时间：2019/12/11 Scanning Probe Microscope High Spatial Resolution Hyper Spectrum Urban Target Remote Sensing Technology Optical Spectral Image
	A spectral calibration approach for snapshot image mapping spectrometer (IMS) 会议论文 9TH INTERNATIONAL SYMPOSIUM ON ADVANCED OPTICAL MANUFACTURING AND TESTING TECHNOLOGIES (AOMATT 2018): OPTICAL TEST, MEASUREMENT TECHNOLOGY, AND EQUIPMENT, 2019-01-01 作者: 收藏 \| 浏览/下载：5/0 \| 提交时间：2019/12/30 snapshot image mapping spectrometer hyper-spectral imaging system spectral calibration crosstalk
	An approach for hyperspectral image classification by optimizing SVM using self organizing map 期刊论文 JOURNAL OF COMPUTATIONAL SCIENCE, 2018, 卷号: 25, 页码: 252-259 作者: Jain, Deepak Kumar; Dubey, Surendra Bilouhan; Choubey, Rishin Kumar; Sinhal, Amit; Arjaria, Siddharth Kumar 收藏 \| 浏览/下载：32/0 \| 提交时间：2019/12/16 Self organizing Map(SOM) Support vector Machine(SVM) Classification Hyper-spectral image
	Tensor Nuclear Norm-Based Low-Rank Approximation With Total Variation Regularization 期刊论文 IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2018, 卷号: 12, 期号: 6, 页码: 1364-1377 作者: Chen, Yongyong; Wang, Shuqin; Zhou, Yicong 收藏 \| 浏览/下载：3/0 \| 提交时间：2019/12/11 Low-rank tensor approximation tensor nuclear norm hyper total variation spatial-spectral total variation image denoising
	A novel deep convolutional neural network for spectral-spatial classification of hyperspectral data 会议论文 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 作者: Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D. 收藏 \| 浏览/下载：4/0 \| 提交时间：2019/12/30 Convolution Deep neural networks Extraction Feature extraction Image processing Independent component analysis Neural networks Remote sensing Spectroscopy Competitive performance Deep CNN Deep convolutional neural networks Generalization ability Hyper-spectral classification Hyperspectral Data Hyperspectral remote sensing Spectral-spatial classification Classification (of information)
	Distance-based separability criterion of ROI in classification of farmland hyper-spectral images 期刊论文 2017, 卷号: 10, 页码: 177-185 作者: Tang Jinglei; Miao Ronghui; Zhang Zhiyong; Xin Jing; Wang Dong 收藏 \| 浏览/下载：11/0 \| 提交时间：2019/12/20 distance-based separability criterion near-infrared hyper-spectral image ROI farmland image classification
	Hyperspectral Image Denoising with Segmentation-based Low Rank Representation 会议论文作者: Ma, Jiayi; Jiang, Junjun; Li, Chang 收藏 \| 浏览/下载：2/0 \| 提交时间：2019/12/05 Denoising graph based segmentation hyper-spectral image low-rank representation mixed noise
	Improved non-negative tensor Tucker decomposition algorithm for interference hyper-spectral image compression 期刊论文 science china-information sciences, 2015, 卷号: 58, 期号: 5 作者: Wen Jia; Zhao JunSuo; Ma CaiWen; Wang CaiLing 收藏 \| 浏览/下载：52/0 \| 提交时间：2015/04/03 interference hyper-spectral images LASIS three-dimensional lifting wavelet transform non-negative tensor decomposition image compression
	MONITORING OF DEGRADING GRASSLAND BASED ON HJ-1A-HSI IMAGE 其他 2013-01-01 Chen Gaoxing; Fan Wenjie; Xu Xiru; Deng Mengzhi 收藏 \| 浏览/下载：3/0 \| 提交时间：2015/11/13 DSD method LAI HIS image grassland monitoring hyper-spectral image LEAF-AREA INDEX INNER-MONGOLIA CHINA LAI SYSTEMS
	Level 0 and level 1 data processing for a type of hyper-spectral imager (EI CONFERENCE) 会议论文 2009 International Conference on Optical Instruments and Technology, OIT 2009, October 19, 2009 - October 21, 2009, Shanghai, China Li X.; Yan C. 收藏 \| 浏览/下载：63/0 \| 提交时间：2013/03/25 Hyper-spectral imaging (HSI) is a kind of optical remote sensor that can simultaneously obtain spatial and spectral information of ground targets. We are now designing a data processing system for a type of space-borne push-broom HSI then it performs radiometric and spectral calibration based on the ground calibration results and onboard calibration collection. The detailed algorithms for bad pixel replacement which has 128 spectral channels covering the spectral range from 400nm to 2500nm. With its large amount of spectral channels radiometric and spectral calibration were presented. After processing the HSI collects large volume of spectral imaging data need to be efficiently and accurately processed and calibrated. In this paper the digital numbers downlinked from the spacecraft can be converted into at-sensor absolute spectral radiance of ground targets the detailed Level 0 and Level 1 data processing steps for the HSI were presented. The Level 0 processing refers to a set of tasks performed on the data downlinked from the spacecraft thus providing accurate quantified spectral imaging data for various applications. 2009 SPIE. including decoding to extract science data separating the science data into files corresponding to different tasks (e.g. ground imaging dark imaging and onboard calibration) checking data integrity and instrument settings data format conversion and Level 0 files creation. The Level 1 processing performs several steps on Level 0 data. Firstly it corrects the image artifacts (mostly the SWIR smear effect) subtracts the dark background and performs the bad pixel replacement according to the prelaunch measurement

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