Image Processing Procedures Based on Multi-Quadratic Dynamic Programming
This paper summarizes the doctoral dissertation  of the author. The main subject of this thesis is the study and development of a method for edge preserving in image smoothing, which is developed based on multi-quadratic dynamic programming procedure for maximum a posteriori probability estimation. Additionally, a new non-convex type regularization is proposed, with ability to flexibly set a priori preferences, using different penalties for various ranges of differences between the values of adjacent image elements. Procedures of image processing, as presented here, consider heterogeneities and discontinuities in the source data, while retaining high computational efficiency of the dynamic programming procedure and Kalman filter-interpolator. Comparative study shows, that proposed algorithms has high accuracy to speed ratio, especially in the case of high-resolution images.
Pham Cong Thang (2016). Parametric Image Processing Procedures Based on Multi-Quadratic Dynamic Programming. Ph.D. dissertation, Tula State University, Russia, 140 pages.
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