Programmable logic is emerging as an attractive solution for many digital signal processing application. This paper presents an FPGA implementation of an iterative image restoration technique. The simulation results show the speedup that can be achieved by implementing this algorithm on reconfigurable hardware as compared to the implementation of the algorithm using software. The process from design entry to files download are introduced.
Image fusion is a technique of combining complementary information from multiple images originated from single or different sources to form single fused image. This fused image has better quality compared to the original input images. In this paper a new fusion technique based on independent component analysis (ICA) and IHS transformation is proposed. A comparison of this new technique with PCA, IHS, and ICA-based fusion techniques is given. Ikonos-2 data are used to test the new and other three techniques. Four evaluation criteria are used for quantitative assessment the quality of the obtained fused images. To assess the spectral quality the spectral discrepancy () and correlation coefficients () are used. For spatial quality assessment high pass correlation coefficients () and information entropy () are used. The results of the new technique show higher performance compared to the other techniques.
The primary goal of visual tracking is to provide a computerized system resembling the capabilities of the human eye. Motion detection is used in many applications and its integration as a facility within a vision system offers many potential benefits. We introduced an investigation of target tracking techniques; two different target tracking algorithms were implemented. The first is Covariance-based target tracking technique and the second is Hu Moments-based target tracking technique. The implemented tracking techniques were investigated and analyzed to determine which algorithm is suitable. Both algorithms were enhanced by achieving segmentation process using the region growing technique and building an adaptive window size that surrounds the target to overcome the problem of scaling. The experimental results show that the enhancement was very efficient not only in target tracking but also in overcoming the occlusion problem.
This paper deals with one of the most critical computing problems which is Cryptography application, it is one of the problem that needs high computing power resources. This paper introduces Symmetric Key Cryptography using DES (Data Encryption Standard) algorithm and employs a computing Grid for dealing with this problem. It presents a Grid for solving this problem that has been implemented by Alchemi which is an open source project developed at the University of Melbourne, which provides middleware for creating an enterprise grid computing environment by harnessing windows machines. The grid has been tested and results have been analyzed, there was an increase in performance over the single processor, but the performance improvement is limited by the I/O and communication overhead.
This paper introduces implementation of some image restoration techniques, which can be applied for satellite images. These techniques are, inverse filter, iterative method, wiener filter, regularized deconvolution filter and wavelet-based method. The restoration techniques are applied on several satellite images associated with atmospheric turbulence blur at different variance of additive noise to check the performance of each technique and its capability to restore the degraded image as close as possible to the original image. Also, comparison studies between these techniques are introduced based on measures like Peak Signal-to-Noise Ratio (PSNR) and Root Mean Square Error (RMSE). The experimental results show that: the wavelet method is the most suitable restoration technique for satellite images, since it gives high PSNR and small RMSE with respect to the other restoration techniques.
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