{"ID":2865377,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.22392","arxiv_id":"2509.22392","title":"Gradient-based multi-focus image fusion with focus-aware saliency enhancement","abstract":"Multi-focus image fusion (MFIF) aims to yield an all-focused image from multiple partially focused inputs, which is crucial in applications cover sur-veillance, microscopy, and computational photography. However, existing methods struggle to preserve sharp focus-defocus boundaries, often resulting in blurred transitions and focused details loss. To solve this problem, we propose a MFIF method based on significant boundary enhancement, which generates high-quality fused boundaries while effectively detecting focus in-formation. Particularly, we propose a gradient-domain-based model that can obtain initial fusion results with complete boundaries and effectively pre-serve the boundary details. Additionally, we introduce Tenengrad gradient detection to extract salient features from both the source images and the ini-tial fused image, generating the corresponding saliency maps. For boundary refinement, we develop a focus metric based on gradient and complementary information, integrating the salient features with the complementary infor-mation across images to emphasize focused regions and produce a high-quality initial decision result. Extensive experiments on four public datasets demonstrate that our method consistently outperforms 12 state-of-the-art methods in both subjective and objective evaluations. We have realized codes in https://github.com/Lihyua/GICI","short_abstract":"Multi-focus image fusion (MFIF) aims to yield an all-focused image from multiple partially focused inputs, which is crucial in applications cover sur-veillance, microscopy, and computational photography. However, existing methods struggle to preserve sharp focus-defocus boundaries, often resulting in blurred transition...","url_abs":"https://arxiv.org/abs/2509.22392","url_pdf":"https://arxiv.org/pdf/2509.22392v1","authors":"[\"Haoyu Li\",\"XiaoSong Li\"]","published":"2025-09-26T14:20:44Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false,"code_links":[{"ID":609268,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2865377,"paper_url":"https://arxiv.org/abs/2509.22392","paper_title":"Gradient-based multi-focus image fusion with focus-aware saliency enhancement","repo_url":"https://github.com/Lihyua/GICI","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}