Impulse noise removal using fuzzy logics

• Published in: 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC) pp. 413 - 418
• Main Authors: Rehan Afzal, H. M., Yu, Jun, Kang, Yu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2017
• Subjects: Algorithm design and analysis; Fuzzy logic; Fuzzy Logics; Image De-noising; Image denoising; Image Restoration; Impulse Noise; Noise measurement; Noise reduction; Noise Removal; PSNR; Remove Blurriness; Visualization
• DOI: 10.1109/YAC.2017.7967444

Image denoisig is becoming an essential step for analysis of images which occurs due to the imperfections of sensors or during the transmission of data. A novel algorithm for image denoising is proposed, based on fuzzy logics. Using fuzzy features an algorithm is primed which adaptively removes impulse noises. This algorithm consists of two parts including the detection of noise and the removal of noise. In the first part, the fuzzy reasoning concept is introduced to determine the type and intensity of noise. In the second part, noise is removed using fuzzy filter according to the membership functions modeled in the previous part. The algorithm can remove both type of impulse noises such as fixed and random impulse noises. This algorithm has been tested on several standard images and compared with existing denoising algorithms with the help of PSNR(peak to signal noise ratio) and quantitative analysis. This novel algorithm demonstrates its robustness and accuracy under differrent noise scales.