Enhancing Performance of Image De-noising via Adaptive Hexagonal Structures
Image processing is a very important area. It finds applications in several fields and has been efficiently used in fields like forensic imaging, medical imaging, computer graphics, etc. Normally, we use a square grid for the processing of images. However, rectangular image de-noising takes into consideration four neighbour or eight neighbour pixels around the noisy pixel. This limits the performance of a de-noising method to the visual correctness of the four or eight neighbouring pixels. This can be enhanced with the help of a hexagonal structure based de-noising technique. The quality of the image is distorted, when an image is affected by salt and pepper noise. Due to this, the homogeneity among the pixels is broken. However, this study introduces a new method for de-noising images with hexagonal pixel structures. De-nosing algorithm operated on the image with hexagonal pixels improves Signal–to-Noise Ratio by more than 8% compared to the denoising carried out using a square -pixel algorithm.
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