A random-valued impulse noise removal algorithm via just noticeable difference threshold detector and weighted variation method

Abstract

The paper presents a random-valued impulse noise (RVIN) removal algorithm by using distinct impulse noise detection and correction stages. In the noise detection phase, the local luminance adaption of an image is used to detect the obvious noise pixels firstly, and the just noticeable difference (JND) is introduced to detect the noise pixels hiding in image details afterward. In the noise candidate correction phase, the obvious noise pixels, almost distributing in the smooth region, are restored by a weighted mean filter. For the noise candidates hiding in image details, we adopt a weighted detail-preserving variation method to restore them. Since human visual perception and detail-preserving are taken into account during the course of the noises detection and restoration, our method outperforms some existing methods, both in visual and quantitative measurements.

Keywords:

• Random-valued impulse noise
• just noticeable difference
• variation method

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Natural Science Foundation of Anhui Province [grant number 1708085QF147]; National Natural Science Foundation of China (NSFC) [grant number 61701006]; University Natural Science Research Project of Anhui Province [grant number KJ2015A234].

Notes on contributors

Zhu Zhu

Zhu Zhu received his BS degree in Science and Technology of Electronic Information from Huaibei Normal University, Huaibei, China, in 2007. He received his MS degrees in Optical Engineering from Soochow University, Suzhou, China, in 2010. He received his PhD degrees in Instrument Science and Technology from Southeast University, Nanjing, China, in 2013. He is currently an associate professor in Anqing Normal University. His research interests include digital image processing, pattern recognition, and image quality assessment.

Xiaoguo Zhang

Xiaoguo Zhang received the M.S. and Ph.D. degrees in the CAD and GPS/DR/MM integrated vehicle navigation field from Southeast University, Nanjing, China, in 1998 and 2001 respectively. He is currently with the School of Instrument Science and Engineering, Southeast University, as an associate professor and master graduate supervisor. His research interests include digital image processing, pattern recognition, and image quality assessment.