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 ...

The term hyperspectral is used to refer to spectra consisting of large number of narrow, contiguously spaced spectral bands. In the field of remote sensing, the term hyperspectral is also used interchangeably with other terms such as spectroscopy, spectrometry, spectroradiometry and rarely ultraspectral. Spectroscopy is a branch of physics concerned with the production, transmission, measuremen...

Hyperspectral images are one of the most important fundamental and strategic information resources, imaging the same ground object with hundreds of spectral bands varying from the ultraviolet to the microwave. With the emergence of huge volumes of high-resolution hyperspectral images produced by all sorts of imaging sensors, processing and analysis of these images requires effective retrieval t...

For hyperspectral image research, spectral characteristic retainment is more important than the spatial details retainment, so it is necessary to evaluate the spectral influence of hyperspectral image compressed sensing. In this paper, the researchers select a hyperspectral remote sensing image PROBE CHRIS with abundant coastal wetland ground objects to analyze spectral fidelity of wavelet tran...

This chapter focuses on the problem of recovering a hyperspectral image descriptor based upon harmonic analysis. It departs from the use of integral transforms to model hyperspectral images in terms of probability distributions. This provides a link between harmonic analysi and affine geometric transformations between object surface planes in the scene. Moreover, the use of harmonic analysis pe...

This paper introduces a hyperspectral image classification approach by using pixel spatial relationship. In hyperspectral images, the spatial relationship among pixels has been shown to be important in the exploration of pixel labels. To better employ the spatial information, we propose to estimate the correlation among pixels in a hypergraph structure. In the constructed hypergraph, each pixel...

Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized ...

This paper studies a new Bayesian optimization algorithm for fusing hyperspectral and multispectral images. The hyperspectral image is supposed to be obtained by blurring and subsampling a high spatial and high spectral target image. The multispectral image is modeled as a spectral mixing version of the target image. By introducing appropriate priors for parameters and hyperparameters, the fusi...