Abstract
This paper describes the development of Fuzzy-based Modified Median (FMM) filter which uses a simple membership function for fuzzification of intensity values of the corrupted image using which noise detection is performed in the order of a 3 × 3 overlapping sliding window. If the central pixel of the window is found corrupted, this filter computes four different medians on its neighbourhood pixels using which the filter estimates the original value of the corrupted pixel. This filter has produced higher Peak Signal-to-Noise Ratio (PSNR) and Mean Structural Similarity Index Matrix (MSSIM) values comparable with other high performing median-based fixed-value impulse noise filters. The added advantage of the filter is its reduced computational speed and complexity. This filter provides denoising solutions to the application domains like Document Imaging, SEM and TEM images wherein the images are often corrupted with fixed-value impulse noise.
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Authors wish to place on record the financial assistance received in the form of a Major Research Project from UGC, New Delhi.
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Shanmugavadivu, P., Eliahim Jeevaraj, P.S. (2014). A Robust Fuzzy-Based Modified Median Filter for Fixed-Value Impulse Noise. In: Mat Sakim, H., Mustaffa, M. (eds) The 8th International Conference on Robotic, Vision, Signal Processing & Power Applications. Lecture Notes in Electrical Engineering, vol 291. Springer, Singapore. https://doi.org/10.1007/978-981-4585-42-2_27
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DOI: https://doi.org/10.1007/978-981-4585-42-2_27
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