This paper address the detection of dust storms based on a probabilistic analysis of multispectral images. We develop a feature set based on the analysis of spectral bands reported in the literature. These studies have focused on the visual identification of the image channels that reflect the presence of dust storms through correlation with meteorological reports. Using this feature set we dev...

In this paper we propose a novel algorithm for the pansharpening of multispectral images based on the use of a Total Variation (TV) image prior. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images, and uses the sensor characteristics to model the observation process of both panchromatic and multispectral ...

Compression of remote-sensing images can be necessary in various stages of the image life, and especially on-board a satellite before transmission to the ground station. Although on-board CPU power is quite limited, it is now possible to implement sophisticated real-time compression techniques, provided that complexity constraints are taken into account at design time. In this paper we consider...

Obtaining detailed and reliable data about local economic livelihoods in developing countries is expensive, and data are consequently scarce. Previous work has shown that it is possible to measure local-level economic livelihoods using high-resolution satellite imagery. However, such imagery is relatively expensive to acquire, often not updated frequently, and is mainly available for recent yea...

Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations ...

This paper presents a system that integrates biologically and geometrically inspired approaches to detecting objects from hyperspectral and/or multispectral (HS/MS), multiscale, multiplatform imagery. First, dimensionality reduction methods are studied and used for hyperspectral dimensionality reduction. Then, a biologically inspired method, SLEGION (Spatial Locally Excitatory Globally Inhibito...

-Land use classification is an important part of many remote-sensing applications. A lot of research has gone into the application of classifiers to remote-sensing images. Multi-spectral satellite imagery is an economical, precise and appropriate method of obtaining information on land use and land cover. In this paper, we have proposed an efficient technique for classifying the multispectral s...

Multispectral imaging—a method for acquiring image data over a series of wavelengths across the light spectrum—is becoming a valuable tool within the cultural Correspondence: Melissa Terras, Department of Information Studies, Foster Court, University College London, Gower Street, WC1E 6BT, London. E-mail: [email protected] Digital Scholarship in the Humanities The Author 2015. Published by Oxf...