Compressió d'imatges hiperespectrals mitjançant transformades Wavelet per aplicacions de teledetecció i sistemes d'informació geogràfica

The increasing availability of a great number of remote sensing (RS) images (multi and hypersectral), orthophotos, etc, and their use in Geographical Information Systems (GIS), is leading to perform research of compressing techniques in order to achieve, appropriately compressed formats of these images to be used in RS (classification, photo interpretation etc) and GIS (spatial analysis, etc) beyond their simple visualization. Similarly there is a growing consensus concerning the use of watermarking techniques to ensure the integrity and the origin of source images. The present project is aimed at exploring several techniques of image compression and marking, performing them in a GIS environment by means of compression formats (lossy and lossless) with the following attributes: 1) high speed of data recovering in any image area and zoom; 2) optional respect to given image regions where no information loose should be produced; 3) in the case of loosy compression, loose quantification when the image contains physical parameters as temperature, radiance, elevation, etc...4) respect of nodata regions, which should be maintained at any comprenssion level: 5) availability of compression of monoband and multiband (either multi or hiperspectral) images; 6 to reach high compression ratios while maintaining image quality; 7) invisible watermarking able to resist image compressionStudies on the consequences of the different parameters and compression ratios implemented experimented on images of several types, will also be part of this project. Such studies will be carried out on both the visual analysis and the digital analysis, with the goal to establish a theory for validating schemes as the one propped