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19 November 2012 Test environment for image synthesis of a single pixel camera
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Compressed sensing as an imaging method has become very popular among scientists and is becoming more and more popular among hardware manufacturers. There are many hardware variants of single-pixel compressed sensing based camera and there are many algorithms of sparse signal approximations. This fact makes it appear more and more applications of compressive imaging. Recently, many algorithms for signal reconstruction have been developed, however, all of them need many parameters to be properly set before using. Setting proper parameters is crucial for preparing a real model of the single pixel camera as well as for fast and efficient image synthesis. Because of high complexity of image recovery algorithms, image synthesis process needs to be optimized. Optimization of signal acquisition and processing parameters can be achieved running various camera simulations. In the paper we present the integrated test environment for image synthesis of the single pixel camera and the test results of simulations run with various configurations and parameters values. We used two combined adaptive methods for image reconstruction - the Newton method and the conjugate gradient method. Test environment allows to run two kinds of tests. The first test type is simulation of various parameters of acquired signal e.g. bit resolution. Image geometric transformation like rotation is the second type of tests. Simulation results include quality parameters values of MSE, PSNR and SSIM and image reconstruction time. Integrated test environment can be used during the process of hardware selection as well as during camera tests with real signals.
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Marcin Kowalski, Marek Piszczek, and Mieczyslaw Szustakowski "Test environment for image synthesis of a single pixel camera", Proc. SPIE 8542, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VI, 85421G (19 November 2012);

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