This research work presents a supervised classification framework for hyperspectral data that takes into account both spectral and spatial information. Texture analysis is performed to model spatial characteristics that provides additional information, which is used along with rich spectral measurements for better classification of hyperspectral imagery. The moment invariants of an image can de...

Segmentation methods, combining spectral and spatial information, are essential for analysis of multi-spectral images. In this article, we propose such a method based on statistical pattern recognition algorithms and a combined classifier approach. A set of experiments is presented with multi-spectral images of detergent laundry powders acquired by imaging cross-sections with scanning electron ...

We investigate the feasibility of designing spectral diversity filters using spherical beam volume holograms. Our experimental results qualitatively show the separation of the information of different incident wavelength channels using spherical beam volume holograms. The major trade-off in using these holograms is between the degree of spatial spectral diversity and the number of allowed spati...

introduction monitoring of salt lake dry areas is an important parameter for sustainable development and environmental protection. monitoring of dried areas of the salt lake requires extraction of thematic maps at different times. powerful tool for remote sensing of the earth different ecosystems, such as playa environments, is to produce valuable and useful data. the major causes of widespread...

Imaging spectroscopy data provides information that is both spatially and spectrally rich. However, hyperspectral classification and identification procedures are generally based solely on the spectral data. The Sspace concept treats the spectrum as a ’spatial’ dimension thereby facilitating the exploration of a relationship between the spectral and spatial image domains. This paper presents th...

Recent demonstrations of teleportation have transferred quantum information encoded into either polarization or fieldquadrature degrees of freedom (DOFs), but an outstanding question is how to simultaneously teleport quantum information encoded into multiple DOFs. We describe how the transverse-spatial, spectral and polarization states of a single photon can be simultaneously teleported using a...

Two dimensional mid-infrared upconversion imaging provides unique spectral and spatial information showing good potential for mid-infrared spectroscopy and hyperspectral imaging. However, to extract spectral or spatial information from the upconverted images an elaborate model is needed, which includes non-collinear interaction. We derive here a general theory providing the far field of the upc...

Hyperspectral image (HSI) denoising is essential for enhancing HSI quality and facilitating HSI processing tasks. However, the reduction of noise in HSI is a difficult work, primarily due to the fact that HSI consists much more spectral bands than other remote sensing images. Therefore, comparing with other image denoising jobs that rely primarily on spatial information, efficient HSI denoising...

This paper describes a method for post-processing classified images to enable generalisation to be performed whilst maintaining or improving the accuracy of region boundaries. This is achieved by performing region growing, and incorporates both spatial context and spectral information. In contrast, few classifiers use any spatial context, and many post-processing techniques, such as iterative m...