Simplification and Performance Enhancement of Image Processing via Hexagonal Grids

Author(s)	Komal Middha, Dr. Banita -
Country	India
Abstract	This research explores the simplification and performance enhancement of image processing algorithms through the adoption of hexagonal grid representation. Unlike conventional square pixel structures, hexagonal grids offer superior sampling efficiency, uniform connectivity, and reduced redundancy in neighborhood operations. By leveraging these properties, the study demonstrates how computational complexity can be minimized while improving accuracy in edge detection, filtering, and segmentation tasks. Sobel edge detection is effective for highlighting strong, linear boundaries but is limited by its sensitivity to noise and inability to capture finer textures. In contrast, the Canny method delivers cleaner, thinner, and more continuous edges by integrating smoothing and thresholding techniques, making it more robust and precise. Simulation results highlight that hexagonal representation enhances visual quality, reduces processing time, and provides a more natural approximation of circular features, making it a promising alternative for advanced image processing applications.
Keywords	Hexagonal pixel grid, Image processing algorithms, Spatial sampling, Edge detection, Computational efficiency
Field	Computer Applications
Published In	Volume 8, Issue 1, January-February 2026
Published On	2026-01-27
DOI	https://doi.org/10.36948/ijfmr.2026.v08i01.67490

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