In this paper, we first introduce a general approach for context-aware patch-based image inpainting, where textural descriptors are used to guide and accelerate the search for well-matching (candidate) patches. A novel top-down splitting procedure …
The KPCA algorithm is widely used for feature extraction of hyperspectral images. One of the disadvantages of KPCA is that its sequential implementations have long run time due to their relatively large computational complexity. In this paper, a GPU …
A novel discriminative supervised neighborhood preserving embedding (DSNPE) method is proposed for feature extraction in classifying hyperspectral remote sensing imagery. DSNPE can preserve the local manifold structure and the neighborhood structure. …
Recent advances in sensor technology have led to an increased availability of hyperspectral remote sensing data at very high both spectral and spatial resolutions. Many techniques are developed to explore the spectral information and the spatial …
For the classification among different land-cover types in a hyperspectral image, particularly in the small-sample-size problem, a feature extraction method is an approach for reducing the dimensionality and increasing the classification accuracy. A …