classification

Context-aware patch-based image inpainting using Markov random field modeling

In this paper, we first introduce a general approachfor context-aware patch-based image inpainting, where texturaldescriptors are used to guide and accelerate the search forwell-matching (candidate) patches. A novel top-down splittingprocedure …

Generalized graph-based fusion of hyperspectral and LiDAR data using morphological features

Nowadays, we have diverse sensor technologies and image processing algorithms that allow one to measure different aspects of objects on the Earth [e.g., spectral characteristics in hyperspectral images (HSIs), height in light detection and ranging …

Hyperspectral and LiDAR data fusion: outcome of the 2013 GRSS data fusion contest

The 2013 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC) of the IEEE Geoscience and Remote Sensing Society aimed at investigating the synergistic use of hyperspectral and Light Detection And Ranging (LiDAR) data. The data …

Semisupervised local discriminant analysis for feature extraction in hyperspectral images

We propose a novel semisupervised local discriminant analysis method for feature extraction in hyperspectral remote sensing imagery, with improved performance in both ill-posed and poor-posed conditions. The proposed method combines unsupervised …

Semisupervised local discriminant analysis for feature extraction in hyperspectral images

We propose a novel semisupervised local discriminant analysis method for feature extraction in hyperspectral remote sensing imagery, with improved performance in both ill-posed and poor-posed conditions. The proposed method combines unsupervised …

Two-stage denoising method for hyperspectral images combining KPCA and total variation

This paper presents a two-stage denoising method for hyperspectral image (HSI) by combining kernel principal component analysis (KPCA) and total variation (TV). In the first stage, we use KPCA denoising to reduce spectrally uncorrelated noise. In the …

Classification of hyperspectral data over urban areas using directional morphological profiles and semi-supervised feature extraction

When using morphological features for the classification of high resolution hyperspectral images from urban areas, one should consider two important issues. The first one is that classical morphological openings and closings degrade the object …

Feature extraction for hyperspectral images based on semi-supervised local linear discriminant analysis

We propose a novel semi-supervised local discriminant analysis (SELD) method for feature extraction in hyperspectral remote sensing imagery. The proposed method combines a supervised method (Linear Discriminant Analysis (LDA)) and an unsupervised …

Spatiogram features to characterize pearls in paintings