Title: An adaptive median filtering of visual product image based on gradient direction information
Authors: Kai Liu
Addresses: Wuhan Technical College of Communications, Wuhan, Hubei, China
Abstract: In order to overcome the problems of long filtering process, low signal-to-noise ratio of output results and low integrity of image information in traditional image median filtering methods, a new research method of visual product image adaptive median filtering based on gradient direction information is proposed in this paper. Based on the digital representation of the visual product image, the gradient direction information method is used to extract the noise information in the visual product image, so as to improve the quality of image filtering. Finally, the adaptive median filtering of visual product image is completed by processing the median and extreme values of visual product image. The simulation results show that the filtering process of this method takes 0.25-0.45 min, the signal-to-noise ratio can reach 85 dB, and the integrity of image information varies from 97.5% to 98.2%, which proves that it effectively realises the design expectation.
Keywords: gradient direction information; visual product image; adaptive median filter; noise extraction.
International Journal of Product Development, 2022 Vol.26 No.1/2/3/4, pp.206 - 215
Received: 07 Oct 2021
Accepted: 15 Mar 2022
Published online: 07 Sep 2022 *