Insulator Image Denoising Based on the Simplified PCNN Model

Abstract:

A new denoising method was proposed in the paper according to the characteristics of insulator infrared image with impulse noise. First, based on the pulse coupled neural network (PCNN) to detect the location of the impulse noise pixels, while maintaining the same non-noise pixels. and then according to the characteristics of the impulse noise, the window size of the filter was adaptively determined by calculating the noise intensity of the image. The pixels with maximum and minimum gray value in filtering window are excluded, using the left pixels similarity calculation out weights. A new weighted filtering algorithm is used to filter noise pixels. The experiments show that the method is better than the median filter in peak signal-to-noise ratio (PSNR), and has better image edge details protection ability.

• Periodical: Advanced Materials Research (Volumes 718-720)
• Pages: 2092-2098
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.718-720.2092
• Online since: July 2013
• Authors: Dan Li, Hong Ying He, Yi Jia Cao, Dian Sheng Luo
• Keywords: Image De-Noising, Insulator, PCNN, Pulse Noise

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