Binary image enhancement based on aperiodic stochastic resonance. Issue 12 (1st December 2015)

• Record Type: Journal Article
• Authors: Liu, Jin; Li, Zan
• Is Part Of: IET image processing. Volume 9:Issue 12(2015)
• Page Start: 1033
• Page End: 1038
• Publication Date: 2015-12-01
• Subjects: image enhancement -- image denoising; aperiodic stochastic resonance technique -- ASR technique -- binary image enhancement scheme -- signal enhancement -- PSNR condition -- peak‐signal‐to‐noise ratio condition -- noise elimination -- image processing -- noisy image enhancement; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2014.0709
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : The enhancement of noisy images has been playing a key role in improving the visual effect and the performance of image processing. Traditional methods for image enhancement are mainly focusing on eliminating noise, which cannot acquire good effect under low peak‐signal‐to‐noise ratio (PSNR) conditions. Stochastic resonance (SR), on the contrary, is a technique using noise to enhance signal. Owing to the unique feature of SR, a novel binary image enhancement scheme based on aperiodic SR (ASR) technique is proposed. In this study, the authors take the improvement in PSNR as a measure of the ASR‐based binary image enhancement system, which provides a guideline for the realisation of the ASR system. On this basis, they obtain the PSNR expression of the ASR‐based binary image enhancement system. Simulation results show that the proposed method is superior to the traditional binary image enhancement methods both in visual effect and PSNR performance.