A new classification-based approach for multi-focus image fusion

Samet Aymaz; Şeyma Aymaz; Cemal Köse

A new classification-based approach for multi-focus image fusion

Abstract

Multi-focus image fusion combines two or more images of the same scene with different focus points to create a single detailed fully-focused image. The primary purpose of multi-focus im-age fusion methods is to transfer the correct focus information from the source images to the fused image. This study proposes a new classification mechanism based on focus metrics. This mechanism is designed to classify focused, non-focused and ambiguous regions. The most im-portant feature of the proposed mechanism is that it can detect ambiguous areas and transfer these regions to the fused image correctly. Firstly, each source image is split into non-over-lapping image patches of specified sizes in this study. Then, the generated image patches are classified using created classification mechanism. After the classification process, a decision map is created for each source image. These decision maps are then refined using morpho-logical operations. In the final stage of the designed study, a dynamic fusion rule is proposed. This fusion rule transfers focused and non-focused pixels to the fused image according to a specific rule. In contrast, ambiguous regions, frequently encountered in transitions from fo-cused to non-focused areas, are transferred to the fused image using the gradient-based fusion rule. In this way, the negative effect of the regions that the classification algorithms classified incorrectly on the fused image is reduced. In addition, in this study, the impact of image size on image fusion success is analyzed by using different image sizes in the classification mecha-nism. As a result, the proposed study is evaluated using objective and subjective metrics. The evaluations show that the proposed method is suitable for achieving multi-focus image fusion purposes.

Keywords

References

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Details

Primary Language

English

Subjects

Biochemistry and Cell Biology (Other)

Journal Section

Research Article

Authors

Samet Aymaz ^* This is me
0000-0003-0735-0487
Türkiye

Şeyma Aymaz This is me
0000-0002-8978-4459
Türkiye

Cemal Köse This is me
0000-0002-5982-4771
Türkiye

Publication Date

February 27, 2024

Submission Date

February 13, 2022

Acceptance Date

June 15, 2022

Published in Issue

Year 2024 Volume: 42 Number: 1

IZ

https://izlik.org/JA85LG92ET

Cite

RIS / Bibtex

APA

Aymaz, S., Aymaz, Ş., & Köse, C. (2024). A new classification-based approach for multi-focus image fusion. Sigma Journal of Engineering and Natural Sciences, 42(1), 11-25. https://izlik.org/JA85LG92ET

AMA

1.Aymaz S, Aymaz Ş, Köse C. A new classification-based approach for multi-focus image fusion. SIGMA. 2024;42(1):11-25. https://izlik.org/JA85LG92ET

Chicago

Aymaz, Samet, Şeyma Aymaz, and Cemal Köse. 2024. “A New Classification-Based Approach for Multi-Focus Image Fusion”. Sigma Journal of Engineering and Natural Sciences 42 (1): 11-25. https://izlik.org/JA85LG92ET.

EndNote

Aymaz S, Aymaz Ş, Köse C (February 1, 2024) A new classification-based approach for multi-focus image fusion. Sigma Journal of Engineering and Natural Sciences 42 1 11–25.

IEEE

[1]S. Aymaz, Ş. Aymaz, and C. Köse, “A new classification-based approach for multi-focus image fusion”, SIGMA, vol. 42, no. 1, pp. 11–25, Feb. 2024, [Online]. Available: https://izlik.org/JA85LG92ET

ISNAD

Aymaz, Samet - Aymaz, Şeyma - Köse, Cemal. “A New Classification-Based Approach for Multi-Focus Image Fusion”. Sigma Journal of Engineering and Natural Sciences 42/1 (February 1, 2024): 11-25. https://izlik.org/JA85LG92ET.

JAMA

1.Aymaz S, Aymaz Ş, Köse C. A new classification-based approach for multi-focus image fusion. SIGMA. 2024;42:11–25.

MLA

Aymaz, Samet, et al. “A New Classification-Based Approach for Multi-Focus Image Fusion”. Sigma Journal of Engineering and Natural Sciences, vol. 42, no. 1, Feb. 2024, pp. 11-25, https://izlik.org/JA85LG92ET.

Vancouver

1.Samet Aymaz, Şeyma Aymaz, Cemal Köse. A new classification-based approach for multi-focus image fusion. SIGMA [Internet]. 2024 Feb. 1;42(1):11-25. Available from: https://izlik.org/JA85LG92ET