SINGLE-PIXEL CAMERA-SIMULATION TOOL AND THE FIRST RESULTS OF ANALYSIS OF IMAGE QUALITY

The present trend of signal processing maintains that according to the Nyquist–Shannon theory a signal must be sampled at a rate at least twice its highest frequency in order to be represented without error. However, it is very common to compress the data just after sensing. This approach is very popular in the field of image acquisition. We compress images registered by a camera trading off signal representation complexity. Thus some of the information is simply thrown away. Sparse signal approximations have become a new tool in signal processing with wide range of applications. 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 based on compressed sensing method, image synthesis process needs to be optimized. 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.