In this paper we present a lossless coding scheme for multispectral images. The algorithm di ers from classical lossless approaches of multispectral image coding (1, 2, 3) in the fact that it is based on an independent coding of spectrally homogeneous regions. Regions that present a common multispectral signature are segmented. Then, spectral prediction is performed within these regions and nal...

Pansharpening aims to obtain high spatial resolution multispectral (MS) images by fusing the and spectral information in low (LR) MS panchromatic (PAN) images. Recently, deep neural network (DNN) based pansharpening methods have been advanced extensively. Although most DNN-based show good performance, it is difficult for them preserve details fused image. In this article, we propose a new metho...

The paper compares different data fusion techniques in order to choose an appropriate technique for accurate urban mapping. Availability of high spatial resolution Ikonos and Quickbird imagery has made accurate mapping of urban areas more feasible. Though Ikonos multispectral images have a good spatial resolution of 4 m, it is often desirable to have an increased spatial resolution for a more a...

Orthogonal subspace projection (OSP) approach has shown success in hyperspectral image classification. Recently, the feasibility of applying OSP to multispectral image classification was also demonstrated via SPOT (Satellite Pour 1'Observation de la Terra) and Landsat (Land Satellite) images. Since an MR (magnetic resonance) image sequence is also acquired by multiple spectral channels (bands),...

The present study was conducted to assess socio-economic impacts of deforestation of Hyrcanian forests in two basins of Do-Hezar and Se-Hezar, northern Iran. To this end, changes in the forest area were detected over the period between 1990 and 2006 based on land use land cover maps derived from Landsat and IRS satellite images. The land use changes were investigated by enhancement of the image...

This paper presents a new method for segmenting multispectral satellite images. The proposed method is unsupervised and consists of two steps. During the rst step the pixels of a learning set are summarized by a set of codebook vectors using a Probabilistic Self-Organizing Map (PSOM, [9]) In a second step the codebook vectors of the map are clustered using Agglomerative Hierarchical Clustering ...

The geometric accuracy of the images acquired by the SEVIRI (Spinning Enhanced Visible and InfraRed Imager) instrument aboard the European geostationary satellites Meteosat-8 (formerly MSG-1) and Meteosat-9 (formerly MSG-2) has been investigated in this study. Level 1.5 image data of the High-Resolution Visible (HRV) band with 1-km Ground Sample Distance (GSD) and several multispectral (MS) ban...