The paper proposes the Qualitative Modelling Toolbox (QuaMo Toolbox), a MATLAB compatible toolbox used to synthesise, analyse, supervise and control dynamic systems described by qualitative models. The nature of the qualitative models become obvious from the fact that they do not refer to the numerically precise signal but to symbolic signal values. Therefore the toolbox is useful in applicatio...

We present in this paper the COSTO toolbox that supports the Kmelia abstract component model. First, an overview of the COSTO toolbox is given. Then the abstract component model Kmelia is presented. One main feature of the toolbox is the connection with existing tools in order to perform the analysis of specification properties. We present this approach for the dynamic aspect analysis; an examp...

An Extension to the Frequency Domain System Identification Toolbox for MATLAB has been developed. It adds a simple-to-use Graphical User Interface to the existing toolbox. It increases numerical stability by using orthogonal polynomials. Both periodic and nonperiodic excitation signals can be used by proper modeling in the frequency domain. Systems in closed loop can also be identified. Objects...

1.0 Introduction The image compression toolbox, written by Satish Kumar, located on the internet at http://www.debugmode.com/imagecmp/icomptbx.htm, is a wavelet based image compression tool. The toolbox contains a collection of functions that are commonly used in wavelet based image compression techniques. The following section gives a description of each function that comprises the image compr...

Hyperspectral imaging can provide both continuously spatial and spectral information of the Earth's surface that allows us mapping of the regional geological and mineral resources information. One of the most successful applications of hyperspectral imaging remote sensing identified was regional geological and mineral resource surveys. A light-weight airborne hyperspectral imaging system (LAHIS...

Onboard compression of hyperspectral imagery is important for reducing the burden on downlink resources. Here we describe a novel adaptive predictive technique for lossless compression of hyperspectral data. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that is competitive with the best results from the literature. Al...

Hyperspectral images have the high spectral resolution rather than to multispectral images. By development of remote sensing technology, the new sensors with hyperspectral capabilities in RS science will be replaced to multispectral imaging. A big advantage of hyperspectral images comparison to that of multispectral images is a continuous spectrum for each image cell that can be derived from im...

With the development of sensor technology, the spectral resolution of remote sensing image is continuously improved. The appearance of the hyperspectral remote sensing is a tremendous leap in the field of remote sensing. The increasing availability of hyperspectral data and image has enriched us with better and finer data and it also enable us a much stronger ability to identify features. Howev...

Low-cost Unmanned Airborne Vehicles (UAVs) equipped with consumer-grade imaging systems have emerged as a potential remote sensing platform that could satisfy the needs of a wide range of civilian applications. Among these applications, UAV-based agricultural mapping and monitoring have attracted significant attention from both the research and professional communities. The interest in UAV-base...

Category decomposition method based on matched filter for un-mixing of mixed pixels: mixels which are acquired with spaceborne based hyperspectral radiometers is proposed. Through simulation studies with simulated mixed pixels which are created with spectral reflectance data derived from USGS spectral library as well as actual airborne based hyperspectral radiometer imagery data, it is found th...