Merging of different data sets is often used in digital image processing to improve the visual and analytical quality of the data. The analyst may need to merge different types of data. In this process, different data such as satellite imagery from the same sensor but with different resolution, satellite imagery from different sensors with varying resolution, digitized aerial photography and sa...

The purpose of multispectral satellite imagery preprocessing for Land Cover Classification is creation of enhanced satellite images before further processing and imagery analysis with final land classification and automated linear object and area border detection for selected classes of objects.

This project seeks to develop the technology to fuse high spatial resolution MultiSpectral Imagery (MSI) with lower spatial resolution, but higher spectral resolution, HyperSpectral Imagery (HSI) to provided enhanced target detection and battlespace characterization. It seeks to push beyond traditional PAN sharpening techniques to develop applications that will increase the accuracy and fidelit...

For multispectral imagery (MSI), spatial registration between bands is a very important part of the overall quality of the MSI product. For some remote sensing imagery, mis-registration of bands greater than about one-quarter of a pixel can be visually noticeable. Based on the successful registration processing developed for the Multispectral Thermal Imager (MTI) (known as edgereg), a derivativ...

A new super resolution Bayesian method for pansharpening multispectral images which incorporates sensor characteristics to model the observation process of both the panchromatic and the multispectral images is presented in this paper. The quality of the pansharpened images is assessed both qualitatively and quantitatively. Preliminary results are very promising: the method succeeded in preservi...

* Corresponding author. Tel.: þ1 956 969 483 E-mail address: [email protected] 1537-5110/$ e see front matter Published by doi:10.1016/j.biosystemseng.2010.07.011 Cotton root rot, caused by the soilborne fungus Phymatotrichum omnivorum, is a major cotton disease in the south western and south central United States. Accurate delineation of root rot infestations is necessary for site-specifi...

This paper proposes a novel multispectral feature extraction method according to the idea of canonical correlation analysis (CCA). Instead of extracting two groups of features with the same pattern (modality) as usual, the work explores another type of application of CCA that for extracting most correlated features from different face modalities to form effective discriminant vectors for recogn...

Using unmanned aircraft systems (UAS) as remote sensing platforms offers the unique ability for repeated deployment for acquisition of high temporal resolution data at very high spatial resolution. Multispectral remote sensing applications from UAS are reported in the literature less commonly than applications using visible bands, although light-weight multispectral sensors for UAS are being us...

The utility of satellite imagery for landslide detection in southwest coastal British Columbia was evaluated by interpretation of orbital imagery (SPOT, IKONOS, and QUICKBIRD) and comparison with large-and medium-scale aerial photography. Satellite imagery was enhanced by simple, repeatable digital image processing techniques (contrast stretches and transformations, merging of images of differe...

Optical remote sensing imagery and orthophoto derived stem density were classified to map coniferous forest cover for a study area located in the Western Hunsrück, Germany. Our objectives were (i) to investigate if hyperspectral data contain more information relevant to classification of species and age classes than multispectral imagery and (ii) to test in what way classification results can b...