The most widely known remote-sensing data are satellite images (typically LANDSAT or other visible imagery), which are used in the geosciences for a multitude of applications, including landuse, urbanization, sea-ice expansion, to name only a few. Commonly, these remote-sensing data are analyzed with the help of commercial software systems (eg. ENVI, ERDAS-IMAGINE). Analysis methods employ the ...

In this paper, a robust and efficient digital image watermarking algorithm using the fast Hadamard transform (FHT) is proposed for the copyright protection of satellite images. This algorithm can embed or hide an entire image or pattern as a watermark such as a company’s logo or trademark directly into the original satellite image. The performance of the proposed algorithm is evaluated using a ...

This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions...

PLEIADES is the highest resolution civilian earth observing system ever developed in Europe. This imagery program is conducted by the French National Space Agency, CNES. It operates since 2012 a first satellite PLEIADES-HR launched on 2011 December 17th, a second one should be launched by the end of the year. Each satellite is designed to provide optical 70 cm resolution coloured images to civi...

Everyday satellite is capturing thousands of images which needs to be classified in a proper way. In this paper, we address the problem of replacing the existing images with the captured one. We provide a new solution by storing only the non-existing part of the image. Though satellite images have been classified in past by using various techniques, the researchers are always finding alternativ...

In this paper, we focus on the global optimization of the satellite imaging chain. The theoretical analysis of the satellite imaging chain optimization is a difficult problem that needs lot of approximations. In order to consider the complex real satellite imaging chain, we propose to address this problem numerically and we present, based on numerical experiments, techniques to optimize the qua...

We study the problem of nding a two-dimensional pattern in a compressed satellite image. We present an algorithm that solves this problem without decompressing the image. The runtime of our algorithm is linear in the sum of the sizes of the compressed image and the pattern, unless the image contains many large parts that match the pattern partially, but not fully | an unlikely situation for sat...