Browsing UMBC Computer Science and Electrical Engineering Department by Author "Xue, Bai"
Now showing items 1-8 of 8
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Crack Extraction for Polycrystalline Solar Panels
Xue, Bai; Li, Fang; Song, Meiping; Shang, Xiaodi; Cui, Dongqing; Chu, Jiaping; Dai, Sui (MDPI, 2021-01-12)Crack extraction of solar panels has become a research focus in recent years. The cracks are small and hidden. In addition, there are particles of irregular shape and size on the surface of the polycrystalline solar panel, ... -
Iterative constrained energy minimization convolutional neural network for hyperspectral image classification
Xue, Bai; Shang, Xiaodi; Zhong, Shengwei; Hu, Peter F.; Chang, Chein-I (SPIE, 2019-05-14)In hyperspectral image classification, how to jointly take care of spectral and spatial information received considerable interest lately, and many spectral-spatial classification approaches have been proposed. Unlike ... -
Iterative Scale-Invariant Feature Transform for Remote Sensing Image Registration
Chen, Shuhan; Zhong, Shengwei; Xue, Bai; Li, Xiaorun; Zhao, Liaoying; Chang, Chein-I (IEEE, 2020-07-22)Due to significant geometric distortions and illumination differences, developing techniques for high precision and robust multisource remote sensing image registration poses a great challenge. This article presents an ... -
Optical Remote Sensing Image Registration Using Spatial-Consistency and Average Regional Information Divergence Minimization via Quantum-Behaved Particle Swarm Optimization
Chen, Shuhan; Xue, Bai; Yang, Han; Li, Xiaorun; Zhao, Liaoying; Chang, Chein-I (MDPI, 2020-09-19)Due to invariance to significant intensity differences, similarity metrics have been widely used as criteria for an area-based method for registering optical remote sensing image. However, for images with large scale and ... -
Subpixel approaches to multispectral and hyperspectral image classification and application
Xue, Bai (2019-01-01)One of major advantages of hyperspectral image processing is subpixel detection that can be used to detect targets at subpixel scale (i.e., subtarget) which cannot be visualized by human eye inspection. This dissertation ... -
Unsupervised automatic target generation process via compressive sensing
Bekit, Adam; Porta, Charles Della; Lampe, Bernard; Xue, Bai; Chang, Chen-I (SPIE, 2019-05-13)Unsupervised target generation for hyperspectral imagery (HSI) have generated great interest in the hyperspectral community. However, most of the current unsupervised target generation algorithms have to process large HSI ... -
Unsupervised hyperspectral band selection in the compressive sensing domain
Lampe, Bernard; Bekit, Adam; Porta, Charles Della; Xue, Bai; Chang, Chein-I (SPIE, 2019-05-14)Band selection (BS) algorithms are an effective means of reducing the high volume of redundant data produced by the hundreds of contiguous spectral bands of Hyperspectral images (HSI). However, BS is a feature selection ... -
Unsupervised iterative CEM-clustering based multiple Gaussian feature extraction for hyperspectral image classification
Xue, Bai; Zhong, Shengwei; Shang, Xiaodi; Hu, Peter F.; Chang, Chein-I (SPIE, 2019-05-14)Recently, many spectral-spatial hyperspectral image classification techniques have been developed, such as widely used EPF-based and composite kernel-based approaches. However, the performance of these types of ...