Target detection is an important issue in the HyperSpectral Image (HSI) processing field. However, current spectral-identificationbased target detection algorithms are sensitive to the noise and most denoising algorithms cannot preserve small targets, therefore it is necessary to design a robust detection algorithm that can preserve small targets. This paper utilizes the recently proposed multi...

Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspectral imaging (HSI) has emerged as a useful, noncontact technique for acquiring spectral and optical properties of tissue. A convolutional neural network (CNN) classifier is developed to classify excised, squamous-cell carcinoma, thyroid cancer, and...

In this paper, a novel multi-task learning (MTL) framework for a series of Gabor features via joint probabilistic outputs of support vector machines (SVM), abbreviated as GF-MTJSVM, has been proposed for Hyperspectral image (HSI) classification. Specifically, we firstly use a series of Gabor wavelet filters with different scales and frequencies to extract spectral-spatial-combined features from...

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and compositi...

We present a new and effective approach for Hyperspectral Image (HSI) classification and clutter detection, overcoming a few long-standing challenges presented by HSI data characteristics. Residing in a high-dimensional spectral attribute space, HSI data samples are known to be strongly correlated in their spectral signatures, exhibit nonlinear structure due to several physical laws, and contai...

The separation of pure polyolefins, polyethylene (PE) and polypropylene (PP), from post-consumer plastic waste is of increasing interest in the last years according to market requirements for their further recycling. In this paper new analytical inspection strategies, based on HyperSpectral Imaging (HSI) in the VIS-NIR and NIR fields (400-1000 and 1000-1700 nm, respectively), have been investig...

With EO-1 Hyperion and MightySat in orbit NASA and the DoD are showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing...

The Current Issue of the Sudanese Journal of Paediatrics (SJP) reflects on the engraved old heritage of the Sudanese to help the needy by highlighting the story of the Hawadith Street Initiative (HSI) [1]. Named after the street on which it was founded, which translates indirectly to “Accidents Lane”, HSI was established in 2012 to meet Sudan’s child health insurance gap by crowdfunding medical...

Hyperspectral image (HSI) denoising is a prerequisite for many subsequent applications. For an HSI, the level and type of noise often vary with different bands and spatial positions, which make it difficult to effectively remove noise while preserving textures and edges. To alleviate this problem, we propose a new total-variation model. The main contribution of the proposed approach lies in tha...