Abstract
There are many modern devices are used to create digital images. These devices use optical effects to create images. Therefore, the image quality depends on quality of optical sensors. Because of the limits of technology, these sensors cannot reconstruct the images perfectly, and always include some defects. One from these defects is noise. The noise reduces image quality and result of image processing. The image noises can be classified into some types: Gaussian noise, Poisson noise, speckle noise and so on. Depending on particular noises, we have efficient methods to remove them. There is no existing a universal method to remove all noises effectively. In this paper, we proposed a method to remove a noise that is popular in biomedicine. This noise can be considered as a combination of Gaussian and Poisson noises. Our method is based on the total variation of an image intensity (brightness) function.
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Dang Ngoc Hoang Thanh. Born 1986. He received his Master degree in the field of Applied Mathematics in 2009 at Belarussian State University, Faculty of Applied Mathematics and Computer Sciences. He received his Bachelor in the field Applied Mathematics in 2008 at Belarussian State University, Faculty of Applied Mathematics and Computer Sciences. He is a lecturer at the Hue College of Industry. Some recent courses: Algorithms, Web and Graphics. His scientific and research interests include the following fields: image and signal processing, computer graphics, web technology.
Sergei Dvoenko. Born 1957. He received his Dr. Sci. degree in 2002 at the Dorodnitsyn Computing Centre of the Russian Academy of Sciences (CC of RAS), in the field of Theoretical Foundations of Informatics (05.13.17 of RAS) with the thesis “Pattern Recognition Methods for Arrays of Interconnected Data”. He received his Ph. D. degree in 1992 after the postgraduate course at the Institute of Control Sciences of the Russian Academy of Sciences (ICS of RAS), in the field of Computer Sciences (05.13.16 of RAS) with the thesis “Learning Algorithms for Event Recognition in Experimental Waveforms”. Since 2003, he is a professor at the Institute of Applied Mathematics and Computer Sciences of the Tula State University (IAMCS of TSU) in the Tula city, Russia. He is a lecturer at the Tula State University. Some recent courses: Data Analysis (Machine Learning and Clustering), Decision Theory, Operational Research, Functional and Logical Programming, System Analysis, Algorithms and Calculus Theory. His scientific and research interests include the following fields: image processing, hidden Markov models and fields in applied problems, machine learning and pattern recognition, cluster analysis and data mining. He has 45 scientific publications (papers in peerreviewed journals and international conference proceedings). He is a member of the Russian “Association for Pattern Recognition and Image Analysis” (RAPRIA).
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Thanh, D.N.H., Dvoenko, S.D. A method of total variation to remove the mixed Poisson-Gaussian noise. Pattern Recognit. Image Anal. 26, 285–293 (2016). https://doi.org/10.1134/S1054661816020231
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DOI: https://doi.org/10.1134/S1054661816020231