Fourier transform‐based windowed adaptive switching minimum filter for reducing periodic noise from digital images. Issue 9 (1st September 2016)

• Record Type: Journal Article
• Authors: Varghese, Justin; Subash, Saudia; Tairan, Nasser
• Is Part Of: IET image processing. Volume 10:Issue 9(2016)
• Page Start: 646
• Page End: 656
• Publication Date: 2016-09-01
• Subjects: adaptive filters -- Fourier transforms -- image denoising -- image filtering -- image restoration -- frequency‐domain analysis -- inverse transforms; Fourier transform‐based windowed adaptive switching minimum filter -- digital image -- spatial domain image restoration -- star‐shaped peak region -- frequency correction -- noisy frequency detection stage -- peak detection -- noise map generation substage -- binary flag image -- origin shifted Fourier transformed image corruption -- noise correction scheme -- periodic noise reduction filter -- inverse Fourier transform operation -- inverse shifting -- corrupted frequency domain image noisy area detection; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2015.0750
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : This paper presents a windowed adaptive switching minimum filter in frequency domain to restore images corrupted by periodic noise. Periodic noise frequencies that spread throughout the spatial domain image concentrate in frequency domain image as star‐shaped peak regions. The proposed algorithm incorporates distinct stages of noisy frequency detection and correction. The noisy frequency detection stage has peak detection and noise map generation sub‐stages to effectively identify noisy peak areas into a binary flag image from the directional image of the origin shifted Fourier transformed corrupted image. The proposed noise correction scheme restores the detected noisy areas of the corrupted frequency domain image with the minimum of nearest possible uncorrupted frequencies. Finally, inverse shifting and inverse Fourier transform operations generates the restored image. Experimental results in terms of subjective and objective metrics demarcate that the proposed periodic noise reduction filter is more effective in restoring images corrupted with periodic noise than other filters used in the comparative study.