Signal and Image Processing for Remote Sensing

Signal processing is an enabling technology that encompasses the fundamental theory, applications, algorithms, and implementations of processing or transferring information contained in many different physical, symbolic, or abstract formats broadly designated as signals. Remote sensing can be defined as any process whereby information is gathered about an object, area or phenomenon without being in contact with it. Image processing is any form of signal processing for which the input is an image. Many image processing and analysis techniques have been developed to aid the interpretation of remote sensing images and to extract as much information as possible from the images. The book "Signal and Image Processing for Remote Sensing" contains eight chapters. First chapter proposes a new method to overcome these limitations by using 1D signal analysis methods. The power quality data compression for remote sensing has been described in the second chapter. Third chapter introduces the basic mixed-integer programming model that arises from the detailed interaction of technologies. A brief description of the InSAR technique, as well as an example of processing chain to generate InSAR DEMs, have been introduced in the fourth chapter. Fifth chapter focuses on the evaluation of the performances of different antenna sensors suitable for Partial Discharge (PD) measurements. Optimized signal separation for 3D-polarized light imageing has been focused in sixth chapter. The overall process to code a digital hologram video and the whole architecture of the service system for digital holograms are explained in the seventh chapter. We discuss various aspects of homomorphic encryption schemes - their definitions, requirements, applications, formal construction, and the limitiations of the current homomorphic encryption schemes in the last chapter.