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  Laboratory of Mathematical Methods of Image Processing Chair of Mathematical Physics |
Ringing analysis
Ringing effect is usually introduced to image after different image processing algorithms. The most often it appears after image and video compression. Depending on image class, compression algorithm and compression level, this artifact can vary from unnoticeable to annoying. Aggressive image sharpening can also result to false edges near sharp edges. In some cases ringing effect can be presented initially in source images, for example, in MRI images. The result of MRI is information about the image in frequency domain. Ringing effect appears after image reconstruction in spatial domain when the MRI sampling rate is low. Another example of initially presented ringing effect is analog television. The transmitted TV signal consists of luminance component (Y) and color components (U and V). The bandwidth for color components is narrower than for luminance component. This results in loss of high frequency information in color components and color ringing. If signal quality is low, ringing effect appears also in luminance component. Ringing effect is also introduced by sharpening filters in modern TV sets. Our goalThe goal of the project is to develop efficient algorithms for ringing detection and suppression. One of the key parts of the project is the Ringing database with images containing ringing effect modeled by various popular algorithms. This database can help us investigate the peculiarity of ringing effect of different types and find its common characteristics. Ringing analysis project is the joint project with Zhejiang University, China for 2011–2013 years. Publications2015I. T. Sitdikov, A. S. Krylov. “Variational image deringing using varying regularization parameter” // Pattern Recognition and Image Analysis, Vol. 25, No. 1, 2015, pp. 96−100. A. V. Umnov, A. S. Krylov, A. V. Nasonov. “Ringing artifact suppression using sparse representation” // Lecture Notes in Computer Science, Vol. 9386, 2015, pp. 35−45. PDF. 2014A. Umnov, A. Nasonov, A. Krylov, Ding Yong. “Sparse method for ringing artifact detection” // In: Proceedings of International Conference on Signal Processing (ICSP2014). IEEE, Hangzhou, China, 2014, pp. 662−667. 2013И. Т. Ситдиков, А. В. Насонов, А. С. Крылов, Динг Йонг. «Параллельная реализация алгоритмов вычисления областей для анализа эффекта ложного оконтуривания на изображениях» // в: Труды 15-й международной конференции "Цифровая обработка сигналов и её применение" (DSPA'2013), т. 2. Москва, 2013, с. 55−58. A. V. Nasonov, A. S. Krylov. “Regularization parameter choice for total variation based image deringing algorithm” // In: 23-th International Conference on Computer Graphics GraphiCon'2013. Vladivostok, Russia, 2013, pp. 87−90. I. T. Sitdikov, A. S. Krylov. “Locally adaptive image deringing” // In: 11-th International Conference “Pattern Recognition and Image Analysis: New Information Technologies”, Vol. 1. Samara, Russia, 2013, pp. 322−325. I. T. Sitdikov, A. V. Nasonov, A. S. Krylov, Ding Yong. “Parallel implementation of area detection algorithms for image ringing artifact analysis” // In: Proceedings of 15-th International Conference "Digital Signal Processing and its Applications" (DSPA'2013). Moscow, Russia, 2013, p. 58. 2012A. V. Nasonov, A. S. Krylov. “Edge quality metrics for image enhancement” // Pattern Recognition and Image Analysis, Vol. 22, No. 1, 2012, pp. 346−353. PDF. А. В. Насонов, А. С. Крылов, А. А. Черноморец, Динг Йонг. «Разработка методики анализа эффекта ложного оконтуривания на изображениях» // в: Труды 14-й международной конференции «Цифровая обработка сигналов и её применение» (DSPA'2012), т. 2. 2012, с. 281−285. PDF. A. A. Chernomorets, A. V. Nasonov. “Deblurring in fundus images” // In: 22-th International Conference on Computer Graphics GraphiCon'2012. Moscow, Russia, 2012, pp. 76−79. PDF. A. V. Nasonov, A. S. Krylov. “Text images superresolution and enhancement” // In: IEEE Proceedings of 5th International Congress on Image and Signal Processing (CISP 2012). China, Chongqing, 2012, pp. 728−731. PDF. A. A. Chernomorets, A. S. Krylov. “Blur detection in fundus images” // In: IEEE Proceedings of 5th International Conference on BioMedical Engineering and Informatics (BMEI 2012). China, Chongqing, 2012, pp. 186−189. PDF. A. V. Nasonov, A. S. Krylov, A. A. Chernomorets, Ding Yong. “Framework for image ringing artifact analysis” // In: Proceedings of 14-th International Conference and Exhibition “Digital Signal Processing and its Applications” (DSPA'2012), Vol. 2. 2012, p. 285. PDF. 2011A. M. Yatchenko, A. S. Krylov, A. V. Nasonov. “MRI medical image ringing detection and suppression” // In: 8th Open German-Russian Workshop “Pattern Recognition and Image Understanding” (OGRW-8-2011). Lobachevsky State University of Nizhny Novgorod, November 21-26, 2011, 2011, pp. 259−262. PDF. A. V. Nasonov, A. S. Krylov. “Image enhancement quality metrics” // In: 21-th International Conference on Computer Graphics GraphiCon'2011. Moscow, Russia, 2011, pp. 128−131. PDF. A. V. Nasonov, A. S. Krylov. “Finding Areas of Typical Artifacts of Image Enhancement Methods” // Pattern Recognition and Image Analysis, Vol. 21, No. 2, 2011, pp. 316−318. PDF. 2009A. V. Nasonov, A. S. Krylov. “Scale-space method of image ringing estimation” // In: Proceedings of International Conference on Image Processing (ICIP'09). Cairo, Egypt, 2009, pp. 2794−2797. PDF. A. S. Krylov, A. V. Nasonov. “Adaptive image deblurring with ringing control” // In: Fifth International Conference on Image and Graphics (ICIG '09). Xi'an, Shanxi, China, 2009, pp. 72−75. PDF. A. S. Krylov, A. V. Nasonov, A. A. Chernomorets. “Combined linear resampling method with ringing control” // In: 19-th International Conference on Computer Graphics GraphiCon'2009. Moscow, Russia, 2009, pp. 163−165. PDF. A. V. Nasonov, A. S. Krylov. “Adaptive Image Deringing” // In: 19-th International Conference on Computer Graphics GraphiCon'2009. Moscow, Russia, 2009, pp. 151−154. PDF. 2008A. Krylov, A. Nasonov. “Adaptive Total Variation Deringing Method for Image Interpolation” // In: Proceedings of International Conference on Image Processing (ICIP'08). San Diego, USA, 2008, pp. 2608−2611. PDF. А. В. Насонов. «Программное повышение разрешения и подавление эффекта Гиббса на изображениях» // в: Сборник аннотаций работ 6-й Курчатовской молодёжной научной школы. Москва, 2008, с. 153. PDF. 2007A. Nasonov, A. Krylov, A. Lukin. “Post-Processing by Total Variation Quasi-Solution Method for Image Interpolation” // In: 17-th International Conference on Computer Graphics GraphiCon'2007. Moscow, Russia, 2007, pp. 178−181. PDF. |
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Ringing effect so known as Gibbs phenomenon in mathematical methods of image processing is the annoying effect in images and video appeared as rippling artifact near sharp edges. This effect is caused by distortion or loss of high frequency information in image. It can be found in images of different classes: MRI images, compressed images, oversharpened images, images transmitted over analog channel etc.