Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels. Spectral unmixing methods can be employed to estimate the fractions of reflected light from the different objects within the pixel area. However, spectral unmixing does not pr...

Pose-invariant face recognition remains a challenging problem, especially when the pose change is large. Previous studies use either spatial or spectral information to address this problem. In this paper, we propose an algorithm that uses spatial and spectral information simultaneously to deal with large pose changes. We first learn 3D models from 2D images. We then use these 3D models to gener...

Data fusion methods are often employed to balance contradiction between spectral information and spatial information of remotely sensed images. The fused images formed by an effective data fusion method based on remotely sensed data should have both high spectral information preservation with Low Spatial Resolution (LSR) images and high spatial information preservation with High Spatial Resolut...

Restricted by technical and budget constraints, hyperspectral images (HSIs) are usually obtained with low spatial resolution. In order to improve the spatial resolution of a given hyperspectral image, a new spatial and spectral image fusion approach via pixel group based non-local sparse representation is proposed, which exploits the spectral sparsity and spectral non-local self-similarity of t...

The integration of spatial and spectral responses in hyperspectral image data analysis has been identified as a desirable objective by the remote sensing community. However, most available attempts are based on the consideration of spectral information separately from spatial information, and thus the two types of information are not treated simultaneously. In this paper, we describe our backgr...

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ABSTRACT The analysis of individual X-ray sources that appear in a crowded field can easily be compromised by the misallocation recorded events to their originating sources. Even with small number sources, which none less have overlapping point spread functions, allocation is complex task subject uncertainty. We develop Bayesian method designed sift high-energy photon from multiple leveraging d...