HJ-1-A satellite, developed by China independently, was equipped with two sensors of Hyper Spectral Imager (HSI) and multispectral sensor (CCD). In this paper, we examine the benefits of combining data from CCD data (high-spatial-resolution, low-spectral-resolution image) with HSI data (low -spatial-resolution, high -spectral-resolution image). Due to the same imaging time and similar spectral ...

Acquisition of hyperspectral imagery (HSI) from cameras mounted on terrestrial platforms is a relatively recent development that enables spectral analysis of dominantly vertical structures. Although solar shadowing is prevalent in terrestrial HSI due to the vertical scene geometry, automated shadow detection and restoration algorithms have not yet been applied to this capture modality. We inves...

Well-defined relationships between oligonucleotide properties and hybridization signal intensities (HSI) can aid chip design, data normalization and true biological knowledge discovery. We clarify these relationships using the data from two microarray experiments containing over three million probes from 48 high-density chips. We find that melting temperature (T(m)) has the most significant eff...

We present a framework for hyperspectral image (HSI) analysis validation, specifically abundance fraction estimation based on HSI measurements of water soluble dye mixtures printed on microarray chips. In our work we focus on the performance of two algorithms, the Least Absolute Shrinkage and Selection Operator (LASSO) and the Spatial LASSO (SPLASSO). The LASSO is a well known statistical metho...

This paper presents a hierarchical deep framework called Spectral-Spatial Response (SSR) to jointly learn spectral and spatial features of Hyperspectral Images (HSIs) by iteratively abstracting neighboring regions. SSR forms a deep architecture and is able to learn discriminative spectral-spatial features of the input HSI at different scales. It includes several existing spectral-spatial-based ...

Characterization of the joint (among wavebands) probability density function (pdf) of hyperspectral imaging (HSI) data is crucial for several applications, including the design of constant false alarm rate (CFAR) detectors and statistical classifiers. HSI data are vector (or equivalently multivariate) data in a vector space with dimension equal to the number of spectral bands. As a result, the ...

This paper proposes a novel method of segment-tree filtering to improve the classification accuracy of hyperspectral image (HSI). Segment-tree filtering is a versatile method that incorporates spatial information and has been widely applied in image preprocessing. However, to use this powerful framework in hyperspectral image classification, we must reduce the original feature dimensionality to...

Objective: Somatic symptom disorder (SSD) is characterized by somatic symptoms that are very distressing or cause considerable functional disability. SSD is associated with various medical and psychiatric conditions and imposes high costs on the patient's health care system. Therefore, diagnosis and treatment of SSD are crucial. The Somatic Symptom Scale-8 (SSS-8) is a valuable and brief self-r...

Human immunodeficiency virus (HIV) infection and antiretroviral therapy have been associated with non-alcoholic fatty liver disease (NAFLD), but few studies evaluated whether HIV is an independent risk factor for the development of hepatic steatosis advanced fibrosis. To study prevalence severity fibrosis in people living control outpatients. We conducted a cross-sectional analysis relevant dat...

OBJECTIVES Presence of non-alcoholic fatty liver disease (NAFLD) can predict risks for diabetes, cardiovascular disease and advanced liver disease in the general population. We aimed to establish a non-invasive score for prediction of NAFLD in Han Chinese, the largest ethnic group in the world, and detect whether ethnicity influences the accuracy of such a score. METHODS Liver fat content (LF...