Segmentation and classification are two imperative, yet challenging tasks in image analysis
for remote-sensing applications. In the former, an image is divided into spatially continuous …

Purpose Hyperspectral imaging is an emerging technology recently introduced in medical
applications inasmuch as it provides a powerful tool for noninvasive tissue characterization …

In this paper, an edge-preserving filtering and principal component analysis (PCA)-based
visualization method is proposed for hyperspectral images, in which both global and local …

This paper presents a new approach for hyperspectral image visualization. A bilateral
filtering-based approach is presented for hyperspectral image fusion to generate an …

Conventional hyperspectral image-based automatic target recognition (ATR) systems
project high-dimensional reflectance signatures onto a lower dimensional subspace using …

Hyperspectral Image (HSI) visualization, which aims at displaying as much material
information of original images as possible on a trichromatic monitor with natural color, plays …

In this paper, we propose a model-based approach for the multiresolution fusion of satellite
images. Given the high-spatial-resolution panchromatic (Pan) image and the low-spatial …

Tensor-based robust principal component analysis (PCA) methods are efficient to discover
the low-rank part of a hyperspectral image for reducing redundant information and …

This paper proposes a band-subset-based clustering and fusion technique to improve the
classification performance in hyperspectral imagery. The proposed method can account for …

Image decolorization is known to be an effective way in transferring a color image into a gray
one while well preserving the major information of all three bands. In this paper, a simple yet …