Improved edge gradient image clarity evaluation algorithm

Xiangquan Shen; Maosen Xiao

doi:10.1117/12.3009367

11 October 2023 Improved edge gradient image clarity evaluation algorithm

Xiangquan Shen, Maosen Xiao

Proceedings Volume 12918, Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023); 1291805 (2023) https://doi.org/10.1117/12.3009367
Event: International Conference on Computer Science and Communication Technology (ICCSCT 2023), 2023, Wuhan, China

Abstract

A sharpness evaluation method based on image edge detection is proposed for the problems of poor real-time, weak antiinterference ability and low sensitivity of the traditional gradient evaluation algorithm in the auto-focusing process of digital image processing. The edge pixel points are extracted from the image using an improved adaptive double-threshold Canny operator based on the idea of variance minimization within the OSTU class, and then the extracted image edge pixel points are evaluated. The evaluation function is based on the characteristics of human visual system, and the adaptability and sensitivity of the evaluation function to multiple direction edges are enhanced by improving the evaluation weights of the SMD function for horizontal and vertical direction edges and combining the advantages of the Roberts function for the evaluation of ±45° direction edges. The experimental results show that the improved edge gradient image sharpness evaluation algorithm proposed in this paper has the advantages of good real-time performance, strong anti-noise capability and high sensitivity.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiangquan Shen and Maosen Xiao "Improved edge gradient image clarity evaluation algorithm", Proc. SPIE 12918, Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023), 1291805 (11 October 2023); https://doi.org/10.1117/12.3009367

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KEYWORDS

Image sharpness

Image processing

Detection and tracking algorithms

Digital image processing

Image analysis

Edge detection

Resistance

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