Extraction of Impulse Noise using FPGA

The elimination of noise from images becomes a trending field in image processing. Images may get corrupted by random change in pixel intensity, illumination, or due to poor contrast and can't be used directly. Subsidiary information from such images are extracted by removing the noise, sharpening contrast and detection of the edges by using several filtering techniques. Median filtering is one such nonlinear based method which removes range isolated noise like salt & pepper noise while preserving the edge information. Its miles a computationally intensive operation, so it is hard to put into effect it in actual time. This system introduces a brand-new structure and optimizations for its implementation with FPGAs. The practical consequences show the effectiveness of our improvements allowing actual-time processing and a minimal use of sources. FPGA result is validated by implementing the above algorithm in MATLAB when the images are corrupted by noise models. Citation: L. Soniya, A. V. Kiranmai, Y. Anudeep, V. Venkatesh. "Extraction of Impulse Noise using FPGA." Global Research and Development Journal For Engineering 5.5 (2020): 29 - 34.