PROJECT TITLE :
Binary image enhancement based on aperiodic stochastic resonance
The enhancement of noisy pictures has been taking part in a key role in improving the visual result and therefore the performance of image processing. Ancient methods for image enhancement are mainly focusing on eliminating noise, that cannot acquire smart impact under low peak-signal-to-noise ratio (PSNR) conditions. Stochastic resonance (SR), quite the opposite, may be a technique using noise to reinforce signal. Owing to the unique feature of SR, a novel binary image enhancement scheme primarily based on aperiodic SR (ASR) technique is proposed. During this study, the authors take the improvement in PSNR as a measure of the ASR-based binary image enhancement system, that provides a suggestion for the realisation of the ASR system. On this basis, they get the PSNR expression of the ASR-based binary image enhancement system. Simulation results show that the proposed methodology is superior to the traditional binary image enhancement strategies both in visual effect and PSNR performance.
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