干旱区生态环境知识资源中心(Arid): Unsupervised Detection of Sub-pixel Objects in Hyper-spectral Images via Diffusion Bases

Arid

DOI	10.5220/0008201604960501
	Unsupervised Detection of Sub-pixel Objects in Hyper-spectral Images via Diffusion Bases
	Schclar, Alon; Averbuch, Amir
通讯作者	Schclar, A (corresponding author), Acad Coll Tel Aviv Yaffo, Sch Comp Sci, POB 8401, IL-61083 Tel Aviv, Israel.
会议名称	11th International Joint Conference on Computational Intelligence (IJCCI)
会议日期	SEP 17-19, 2019
会议地点	Vienna, AUSTRIA
英文摘要	Sub-pixel objects are defined as objects which due to their size and due to the resolution of the camera occupy a fraction of a pixel or partially span adjacent pixels. Unsupervised detection of sub-pixel objects can be highly useful in areas such as medical imaging, and surveillance, to name a few. Hyper-spectral images offer extensive intensity information by describing a scene at hundreds and even thousands of wavelengths. This information can be utilized to obtain better sub-pixel detection results compared to those that are obtained using RGB images. Usually, only a small number of wavelengths contain the information that is required for the detection. Furthermore, the intensity images of many wavelengths are noisy and contain very little information. Accordingly, hyper-spectral images must be pre-processed first in order to extract the information that is needed for the sub-pixel detection. This extraction process produces an image where each pixel is represented by a small number of features which allows the application of fast and efficient detection algorithms. In this paper we propose the Diffusion Bases (DB) dimensionality reduction algorithm in order to derive the essential features for the sub-pixel detection. The effectiveness of the DB algorithm facilitates the application of a very simple algorithm for the detection of sub-pixel objects in the feature space. The proposed approach does not assume any distribution of the background pixels. We demonstrate the proposed framework for the detection of cardboard objects in airborne hyper-spectral images of a desert terrain.
英文关键词	Image Processing Subpixel Segmentation Anomaly Detection Unsupervised Sub-pixel Detection Diffusion Bases Dimensionality Reduction Hyper-spectral Sensing
来源出版物	IJCCI: PROCEEDINGS OF THE 11TH INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL INTELLIGENCE
出版年	2019
页码	496-501
ISBN	978-989-758-384-1
出版者	SCITEPRESS
类型	Proceedings Paper
语种	英语
开放获取类型	hybrid
收录类别	CPCI-S
WOS记录号	WOS:000571773900054
WOS类目	Computer Science, Artificial Intelligence
WOS研究方向	Computer Science
资源类型	会议论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/369988
作者单位	[Schclar, Alon] Acad Coll Tel Aviv Yaffo, Sch Comp Sci, POB 8401, IL-61083 Tel Aviv, Israel; [Averbuch, Amir] Tel Aviv Univ, Sch Comp Sci, POB 39040, IL-69978 Tel Aviv, Israel
推荐引用方式 GB/T 7714	Schclar, Alon,Averbuch, Amir. Unsupervised Detection of Sub-pixel Objects in Hyper-spectral Images via Diffusion Bases[C]:SCITEPRESS,2019:496-501.

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