Volume XLII-2/W12
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W12, 161-166, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-161-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W12, 161-166, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-161-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  09 May 2019

09 May 2019

IMAGE SHARPENING WITH BLUR MAP ESTIMATION USING CONVOLUTIONAL NEURAL NETWORK

A. Nasonov, A. Krylov, and D. Lyukov A. Nasonov et al.
  • Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernatics, Lomonosov Moscow State University, Moscow, Russia

Keywords: Blur estimation, Image sharpening, Grid warping

Abstract. We propose a method for choosing optimal values of the parameters of image sharpening algorithm for out-of-focus blur based on grid warping approach. The idea of the considered sharpening algorithm is to move pixels from the edge neighborhood towards the edge centerlines. Compared to traditional deblurring algorithms, this approach requires only scalar blur level value rather than a blur kernel. We propose a convolutional neural network based algorithm for estimating the blur level value.