Abstract
Generally, in digital image processing applications and real-time signal, some unwanted signals capture the image which is termed as noise. It is desirable to be able to perform some image filtering techniques frequently used to reduce or eliminate noise on an image or signal. The two-dimensional spatial median filter is the most commonly used filter for image denoising. The median of a given sequence can be determined by sorting all values in the sequence and by choosing the middle value in the sorted sequence. Commonly, image filters are following up software approach in systems. But hardware implementation prefers in comparison with software implementation for better processing speed. In this paper, we propose an Adaptive Median Filter hardware (AMFh) implementation. Indeed, the 3 × 3, 5 × 5 and 7 × 7 windows techniques are implemented for removal of Salt-Pepper and Impulse Noises from images and simulated using ModelSim (the Verilog language was utilized) and Matlab softwares. We are conducting a study on the effectiveness of the implemented filter, based on two main parameters, the peak signal-to-noise ratio and windows size. PSNR values for a set of benchmark images are calculated to quantify the impact of the proposed AMFh algorithm on the PSNR performance for treated windows size.
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El Khoukhi, H., Idriss, F.M., Yahyaouy, A., Sabri, M.A. (2020). An Efficiency Study of Adaptive Median Filtering for Image Denoising, Based on a Hardware Implementation. In: Bhateja, V., Satapathy, S., Satori, H. (eds) Embedded Systems and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 1076. Springer, Singapore. https://doi.org/10.1007/978-981-15-0947-6_9
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DOI: https://doi.org/10.1007/978-981-15-0947-6_9
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