Fuzzy Noise Removal and Edge Detection on Hexagonal Image

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Abstract

Traditionally images are digitized, processed and displayed in a rectangular grid. But rectangular grid has many inherent ambiguities such as continuity, inter-pixel distance, etc. These ambiguities restrict rectangular grid to obtain optimal results in image processing. This study considers a particular topic of grayscale morphology image processing based on fuzzy discipline for hexagonally sampled images. The proposed research presents a methodology for hexagonally sampled images that consist of processing, and display of processed images on hexagonal grid. Image processing includes fuzzy morphological operations with different sizes, shapes and directional fuzzy structuring elements with an application of noise removal and edge detection. Performance evaluation conducted to demonstrate that hexagonal grid structure coupled with fuzzy morphological image processing is more robust than the rectangular counterpart in many applications.

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