The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-5/W6
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W6, 101–106, 2015
https://doi.org/10.5194/isprsarchives-XL-5-W6-101-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W6, 101–106, 2015
https://doi.org/10.5194/isprsarchives-XL-5-W6-101-2015

  18 May 2015

18 May 2015

MULTI-QUADRATIC DYNAMIC PROGRAMMING PROCEDURE OF EDGE– PRESERVING DENOISING FOR MEDICAL IMAGES

C. T. Pham and A. V. Kopylov C. T. Pham and A. V. Kopylov
  • Institute of Applied Mathematics and Computer Science, Tula State University-Russia

Keywords: Dynamic programming, Bayesian framework, Markov random fields (MRFs), Edges–preserving smoothing, Separable optimization, Potential functions

Abstract. In this paper, we present a computationally efficient technique for edge preserving in medical image smoothing, which is developed on the basis of dynamic programming multi-quadratic procedure. Additionally, we propose a new non-convex type of pair-wise potential functions, allow more flexibility to set a priori preferences, using different penalties for various ranges of differences between the values of adjacent image elements. The procedure of image analysis, based on the new data models, significantly expands the class of applied problems, and can take into account the presence of heterogeneities and discontinuities in the source data, while retaining high computational efficiency of the dynamic programming procedure and Kalman filterinterpolator. Comparative study shows, that our algorithm has high accuracy to speed ratio, especially in the case of high-resolution medical images.