Image focusing on macro photography using fuzzy and Neutrosophic Logic

This paper integrates Neutrosophic logic fuzzy logic, and a multi-echelon inventory model to enhance focus analysis in high- resolution macro images. Macrophotography needs sharp focus to capture fine structures and textures. Traditional techniques often struggle to distinguish between sharp focus and defocus regions when in high resolution close-up image. The integration of Neutrosophic logic enables the inconsistent and indeterminate information through its three valued framework Truth, indeterminate and Falsity. Fuzzy logic complements this by smooth, continuous classification of focus level. To further refine the system’s sensitivity to focus gradient, Heptagonal Fuzzy Numbers are introduced as a part for flexible structure representing subtle transitions of focus intensity. Multi- Echelon Fuzzy Inventory Model is incorporated to optimize the hierarchical allocation of focus- enhancement resources across image regions. This approach highlights the potential of logic -based hybrid systems produce an interpretable focus map and shows significant potential for intelligent image analysis, it is applicable in domains where microscopic or high -detail image clarity is critical such as microstructural analysis, biomedical imaging and machine vision systems.