The image grand tour is a method for visualizing multispectral or multiple registered images. In many settings, several registered images of the same scene are collected. This most often happens when multispectral images are collected, but may happen in other settings as well. A multispectral image can be viewed as an image in which each pixel has a multivariate vector attached. The desired goa...

Multispectral karyotyping analyzes all chromosomes in a single cell by labeling them with chromosome-specific probes conjugated to unique combinations of fluorophores. Currently available multispectral karyotyping systems require the purchase of specialized equipment and reagents. However, conventional laser scanning confocal microscopes that are capable of separating multiple overlapping emiss...

Hyperspectral data potentially contain more information than multispectral data because of their higher spectral resolution. However, the stochastic data analysis approaches that have been successfully applied to multispectral data are not as effective for hyperspectral data as well. Various investigations indicate that the key problem that causes poor performance in the stochastic approaches t...

Multispectral images such as multispectral chemical images or multispectral satellite images provide detailed data with information in both the spatial and spectral domains. Many segmentation methods for multispectral images are based on a per-pixel classification, which uses only spectral information and ignores spatial information. A clustering algorithm based on both spectral and spatial inf...

AUTOMATED precision weed spot spraying in the sugarcane industry has potential to increase production while reducing herbicide usage. However, commercially-available technologies based on sensing of weed optical properties are typically restricted to detecting weeds on a soil background (i.e. detection of green on brown) and are not suited to detecting weeds among a growing crop. Machine vision...

Limits of stereo processing in photogrammetry using image matching techniques are often due to very low capabilities of those procedures regarding aspects of interpretation. For example, if matching aims at recovering terrain surface it would be very helpful to know whether the processed area belongs to an urban area, agricultural land, forest region or other thematic object classes. This is on...

Classical methods for classification of pixels in multispectral images include supervised classifiers such as the maximum-likelihood classifier, neural network classifiers, fuzzy neural networks, support vector machines, and decision trees. Recently, there has been an increase of interest in ensemble learning – a method that generates many classifiers and aggregates their results. Breiman propo...

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 ...

-Automated terrain analysis is required for many practical applications, such as outdoor navigation, image exploitation, remote sensing, reconnaissance and surveillance. In this paper, we present a hierarchical approach to analyze multispectral (MS) imagery for autonomous land vehicle navigation. The approach integrates several strategies to label various terrain classes in these images acquire...

We examine how multispectral imaging can be used to document and improve reading of ancient inscriptions. The research focuses on ostraca, texts written in ink on ceramic potsherds. Three corpora of Hebrew ostraca dating to the Iron Age II were imaged in visible and near infrared light using a state-ofthe-art commercial spectral imager. To assess the quality of images, we used a new quality eva...