Volume XLII-2/W12
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W12, 7-10, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-7-2019
© 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, 7-10, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-7-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  09 May 2019

09 May 2019

INVESTIGATION OF FILTERING AND OBJECTS DETECTION ALGORITHMS FOR A MULTIZONE IMAGE SEQUENCE

N. A. Andriyanov1,2, K. K. Vasil'ev1, and V. E. Dement'ev1 N. A. Andriyanov et al.
  • 1Ulyanovsk State Technical University, 432027 ul. Severny Venets, h. 32, Ulyanovsk, Russia
  • 2Ulyanovsk Institute of Civil Aviation, 432071 ul. Mozhaiskogo, h. 8/8, Ulyanovsk, Russia

Keywords: Filtering, Multizone Images, Random Fields, Doubly Stochastic Models, Model with Multiple Roots, Anomalies Detection

Abstract. The problem of detecting objects on a sequence of images with a complex structure is considered. Optimal and quasi-optimal algorithms for processing multidimensional images have been synthesized and investigated. Improved detection efficiency has been obtained by adequately describing real data using doubly stochastic random fields. The possibility of describing Earth remote sensing data using doubly stochastic models is investigated. The possibility of obtaining significant gains when filtering satellite material and detecting extended objects on it due to the adaptive structure of such models and processing time sequence of multizone images as a single multidimensional dataset is shown. The gains for filtering algorithms in the error variance are about 80% comparing single frame processing, and the gains for detecting algorithms in the signal/noise ratio are about 70% comparing single frame processing.