During the past decades, volume of big data available in remote sensing (RS) applications has grown significantly. In addition, a number related to monitoring human activity are being developed based on this kind data. This considerably increased demand for RS processing methods. sense, scientific community is facing challenge how maximize potential that produced fast and efficient way. particu...

This paper presents an improved edge detection algorithm for facial and remotely sensed images using vector order statistics. The developed algorithm processes coloured images directly without been converted to grey scale. A number of the existing algorithms converts the coloured images into grey scale before detection of edges. But this process leads to inaccurate precision of recognized edges...

as the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. this processing comprises two fundamental and critical steps towar...

The main objective of the Earth Observation Optical Data Calibration and Information Extraction (EODIX) project is to develop advanced ground segment methodologies for optical data calibration and information extraction from a broad family of imaging instruments currently in orbit. EODIX also has an important component related with advanced information extraction from remotely sensed data sets....

different regions [3]. Given a digitized image containing several objects, the image classification process consists of three major phases. AbstractThe analysis of a remote sensing image usually requires the comparison of the analyzed image with another image taken from the same spot. In an automated object identification system for remotely sensed images, thresholding techniques are used to an...

still of wide interest, not only in the analysis of remotely sensed images. We describe a new approach to the extraction of networks of narrow curvilinear features such as road and river networks from remotely sensed MINIMUM COST PATHS images. The approach begins with the identification of points in the image with a high probability of being on the network. In the second stage the broad topolog...

This work introduces an iterative soft cluster refinement method that extensively uses soft cluster evaluation to determine which clusters would discriminate between classes in a classification scheme. This iterative refinement is part of the continuous iterative guided spectral class rejection (CIGSCR) classification method for remotely sensed images. Results indicate that CIGSCR produces good...

Unsupervised change detection using fuzzy cmeans and MRF from remotely sensed images Ming Hao, Hua Zhang, Wenzhong Shi & Kazhong Deng To cite this article: Ming Hao, Hua Zhang, Wenzhong Shi & Kazhong Deng (2013) Unsupervised change detection using fuzzy c-means and MRF from remotely sensed images, Remote Sensing Letters, 4:12, 1185-1194, DOI: 10.1080/2150704X.2013.858841 To link to this article...

the most widespread method to determine temporal and spatial variations of lai in a regional scale is empirical relationships based on the normalized difference of reflectance bands of satellite data. this study was done to evaluate the equations of remotely sensed lai estimation and optimize their parameters. therefore, lai was measured in the field for summer growing season in irrigated field...