The aim of this research is to determine an accuracy assessment of different multispectral gradient-based edge detectors. We will present and evaluate three different approaches: the mean-, the maximumand the multispectral gradient approach. The mean approach determines the overall gradient as the arithmetic mean of all (band-wise) gradient vectors, whereas the maximum approach selects the grad...

This paper is of classification of remote sensed Multispectral satellite images using supervised and unsupervised neural networks. Feature extraction techniques like mean, variance and standard deviation are used. Higher resolution causes higher spectral variability within a class and lessens the statistical separability among different classes in a traditional pixel-based classification. Sever...

Ice cliffs play a key role in the mass balance of debris-covered glaciers, but assessing their importance is limited by lack datasets on distribution and evolution at scales larger than an individual glacier. These are often derived using operator-biased time-consuming manual delineation approaches, despite recent emergence semi-automatic mapping methods. methods have used elevation or multispe...

Remote sensing technologies are one of the major research topics in fusing multisource data and generating high-quality satellite images. In this paper, a new two-dimensional empirical mode decomposition (EMD) method is presented and used to fuse high-resolution panchromatic and multispectral images. First, the new two-dimensional EMD technique, which includes determining the ending criterion o...

Since satellite images with high spatial and spectral quality are highly desired for remote sensing applications, various algorithms have been developed for the fusion of multispectral and panchromatic images. Wavelet transform based mergers have found enormous interest in the fusion community. This paper introduces undecimated filterbanks with lattice structure and applies them to the pansharp...

the major aim of processing satellite images is to prepare topical and effectivemaps. the selection of appropriate classification methods plays an important role. amongvarious methods existing for image classification, artificial neural network method is ofhigh accuracy. in present study, tm images of 1987, and etm+ images of 2000 and 2006were analyzed using artificial fuzzy artmap neural netwo...

Fusion or merging or pansharpening is the digital processing that combines the high spatial and multispectral information to obtain a fused multispectral image that retains the spatial information from the high resolution panchromatic image, as well as the spectral characteristics of the lower resolution multispectral image. Many fusion algorithms were developed and tested on different commerci...

A new approach for object extraction from high-resolution satellite images is presented in this paper. The new approach integrates image fusion, multi-spectral classification, feature extraction and feature segmentation into the object extraction of high-resolution satellite images. Both spectral information from multispectral (MS) images and spatial information from panchromatic (Pan) images a...

Multispectral images acquired by satellites are used to study phenomena on the Earth’s surface. Unsupervised classification techniques analyze multispectral image content without considering prior knowledge of the observed terrain; this is done using techniques which group pixels that have similar statistics of digital level distribution in the various image channels. In this paper, we propose ...