In digital image processing, image segmentation is the most important task. This paper provides an faithful image segmentation algorithm with biologically inspired technique Bacterial Foraging Optimization (BFO) for different images with different size.. The methodology of this paper is to separate R G and B planes of input image and then Revised Bacterial Foraging Optimization Algorithm (RBFOA...

The aim of this work was to develop a system based on modular neural networks and multi-feature texture analysis that will facilitate the automated interpretation of cloud images. This will speed up the interpretation process and provide continuity in the application of satellite imagery for weather forecasting. A series of infrared satellite images from the Geostationary satellite METEOSAT7 we...

The need to transmit or store satellite images is growing rapidly with the development of modern communications and new imaging systems. The goal of compression is to facilitate the storage and transmission of large images on the ground with high compression ratios and minimum distortion. In this work, we present a new coding scheme for satellite images. At first, the image will be downloaded f...

investigation and monitoring of the displacement field derived from deformation is among the important studies in earth science and geophysics topics, which plays a main role in the prevention and praxeology of natural disasters such as earthquake, subsidence, land slide et cetera. here we can mention the several methods in geodetic measurement and deformation monitoring such as spirit leveling...

In recent years, the accelerated growth in the field of computer vision, image fusion, medical imaging, military automatic target recognition, remote cartography and astrophotography has established the need for the development of good image registration technique for the efficient retrieval of interest point area. Image registration is the process of geometrically aligning one image to another...

This paper proposes a methodology for combining satellite images with advection-diffusion models for interpolation and prediction of environmental processes. We propose a dynamic state-space model and an ensemble Kalman filter and smoothing algorithm for on-line and retrospective state estimation. Our approach addresses the high dimensionality, measurement bias, and nonlinearities inherent in s...