Hyperspectral imaging (HSI) electro-optical sensors, with their hundreds of contiguous spectral bands, are a rich data source useful in a variety of applications. Numerous examples have demonstrated their potential. Understanding the characteristics of HSI data is important not only for algorithm design and assessment, but also for accurate modeling in a performance prediction context. Initial ...

In order to improve contrast and restore color for underwater image captured by camera sensors without suffering from insufficient details and color cast, a fusion algorithm for image enhancement in different color spaces based on contrast limited adaptive histogram equalization (CLAHE) is proposed in this article. The original color image is first converted from RGB color space to two differen...

Image segmentation is an important technique in remote sensing hyperspectral image (HSI) processing and application field. It not only can lay a foundation for subsequent object detection, positioning and recognition, but also play an assistant role on HSI data compression and transmission. Level Set which is an effective tool in dealing with image segmentation, has been developed and drawn mor...

Rearing experiments were conducted using several regimes combined with different photoperiods and water temperatures to investigate the role of temperature and photoperiod as environmental cues regulating reproduction in red marbled rockfish, Sebastiscus tertius. The initial gonadosomatic index (GSI) was 1.62±0.32% and that in the 15°C control was 7.01±0.46% at the end of the experiment. The hi...

Our objective is to focus on three areas of application research and transitions. First, we will transition our machine learning-based algorithms and computer code for the determination of bathymetry, bottom type, and water column Inherent Optical Properties from HyperSpectral Imagery (HSI) into a deliverable Message Passing Interface (MPI) program that may be easily used by other research and ...

High spectral dimensionality and the shortage of annotations make hyperspectral image (HSI) classification a challenging problem. Recent studies suggest that convolutional neural networks can learn discriminative spatial features, which play a paramount role in HSI interpretation. However, most of these methods ignore the distinctive spectral-spatial characteristic of hyperspectral data. In add...

17 Detecting beef eating quality in a non-destructive way has been popular in recent years. 18 Among various non-destructive assessing methods, the feasibility of hyperspectral imaging 19 (HSI) system was investigated in this paper. Hyperspectral images of beef samples were 20 collected in an abattoir production line and used for predicting the beef tenderness and pH 21 value. Support vector ma...

Patients with C5 or C6 radiculopathy complain of shoulder area pain or shoulder girdle weakness. Typical idiopathic neuralgic amyotrophy (INA) is also characterized by severe shoulder pain, followed by paresis of shoulder girdle muscles. Recent studies have demonstrated that magnetic resonance neurography (MRN) of the brachial plexus and magnetic resonance imaging (MRI) of the shoulder in patie...

This paper presents the study on identification and classification of food grains using different color models such as L*a*b, HSV, HSI and YCbCr by combining color and texture features without performing preprocessing. The K-NN and minimum distance classifier are used to identify and classify the different types of food grains using local and global features. Texture and color features are the ...

The rapid expansion of remote sensing and information collection capabilities demands methods to highlight interesting or anomalous patterns within an overabundance of data. This research addresses this issue for hyperspectral imagery (HSI). Two new reconstruction based HSI anomaly detectors are outlined: one using principal component analysis (PCA), and the other a form of non-linear PCA calle...