Title: Texture feature extraction method of a multi-focus image based on the gradient fusion rule

Authors: Jie Ding; Guotao Zhao

Addresses: College of Technology, Hubei Engineering University, 432000, China ' School of Foreign Languages, Hubei Engineering University, 432000, China

Abstract: In order to improve the texture detection ability of multi-focus images, a texture feature extraction method based on the gradient fusion rule is proposed. The texture information detection and imaging model of the multi-focus image are constructed. The texture block feature matching model of a multi-focus image is constructed by using the method of region information block detection. Combined with the gradient fusion rule model, the analytic rule function of texture information gradient fusion of multi-focus images is constructed. Through gradient fusion rule distribution and texture information feature decomposition results of images, multi-order moment feature decomposition is adopted to extract texture features from multi-focus images. The simulation results show that the texture feature extraction of multi-focus images by this method has higher output recognition and better texture distribution fusion performance, which improves the imaging quality and texture information enhancement effect of multi-focus images.

Keywords: gradient fusion rules; multi-focus image; texture; feature extraction; region information block detection; analytic rule.

DOI: 10.1504/IJCSM.2022.127828

International Journal of Computing Science and Mathematics, 2022 Vol.16 No.2, pp.181 - 193

Received: 15 Jan 2021
Accepted: 31 Dec 2021
Published online: 19 Dec 2022 *

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