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A Study on Distortion Estimation Based on Image Gradients

Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia
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Author to whom correspondence should be addressed.
Academic Editors: Ying-Ren Chien, Mu Zhou, Liang-Hung Wang and Xun Zhang
Sensors 2022, 22(2), 639; https://doi.org/10.3390/s22020639
Received: 17 December 2021 / Revised: 10 January 2022 / Accepted: 12 January 2022 / Published: 14 January 2022
Image noise is a variation of uneven pixel values that occurs randomly. A good estimation of image noise parameters is crucial in image noise modeling, image denoising, and image quality assessment. To the best of our knowledge, there is no single estimator that can predict all noise parameters for multiple noise types. The first contribution of our research was to design a noise data feature extractor that can effectively extract noise information from the image pair. The second contribution of our work leveraged other noise parameter estimation algorithms that can only predict one type of noise. Our proposed method, DE-G, can estimate additive noise, multiplicative noise, and impulsive noise from single-source images accurately. We also show the capability of the proposed method in estimating multiple corruptions. View Full-Text
Keywords: noise; distortion estimation; multiple corruption estimation; image gradients noise; distortion estimation; multiple corruption estimation; image gradients
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MDPI and ACS Style

Chin, S.C.; Chow, C.-O.; Kanesan, J.; Chuah, J.H. A Study on Distortion Estimation Based on Image Gradients. Sensors 2022, 22, 639. https://doi.org/10.3390/s22020639

AMA Style

Chin SC, Chow C-O, Kanesan J, Chuah JH. A Study on Distortion Estimation Based on Image Gradients. Sensors. 2022; 22(2):639. https://doi.org/10.3390/s22020639

Chicago/Turabian Style

Chin, Sin C., Chee-Onn Chow, Jeevan Kanesan, and Joon H. Chuah. 2022. "A Study on Distortion Estimation Based on Image Gradients" Sensors 22, no. 2: 639. https://doi.org/10.3390/s22020639

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