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Technology for determining reconstruction filter and processing large images

M.A. Drozdov1,2, D.I. Zimin2, S.A. Skuratov2, S.B. Popov1,2, V.A. Fursov1,2
1Image Processing Systems Institute of RAS
2Samara State Aerospace University

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Pages: 175-182.

Abstract:
One of the important stages in imaging of the underlying Earth's surface based on the aerospace monitoring data is the image processing aimed at quality improvement. In this case, at least two problems arise: generation of structure and parameters of the restoration filter and organization of processing of large images.
     In this work, these two problems are solved within the framework of the end-to-end automated technology developed by the authors. The underlying idea of this solution was published in [2]. Then it was applied to the problem of assessing the resolution of a video path based on the fragments of the recorded images [3]. In this paper, this scheme is applied to solving the problem of improving the quality of large images processed by a computing cluster.

Keywords:
processing large image, filter, Earth's surface, aerospace monitoring, restoration filter, computing cluster.

Citation:
Drozdov MA, Zimin DI, Skuratov SA, Popov SB, Fursov VA. Technology for determining reconstruction filter and processing large images. Computer Optics 2003; 25: 175-182.

References:
  1. Soifer VA, ed. Methods of computer image processing. Moscow: "Fizmatlit" Publisher; 2001.
  2. Fursov VA. Identification of models of imaging systems on a small number of observations. Samara: SGAU Publisher; 1998.
  3. Sergeev VV, Fursov VA, Parfenov SI. Estimation of video channel resolvability by fragments of recorded images. Avtometriya 2001; 5: 25-36.
  4. Fursov VA, Popov SB. Parallel image filtering. Proceedings of the Second International Scientific and Practical Seminar “High performance parallel computing on cluster systems” 2002: 307-313.
  5. Popov SB, Soifer VA, Tarakanov AA, Fursov VA. Cluster technology for the formation and parallel filtering of large images. Computer Optics 2002; 23: 75-78.
  6. Popov SB, Skuratov SA. Spatial and streaming parallelization in sliding window image processing technologies. Proceedings of the Third International Scientific and Practical Seminar “High performance parallel computing on cluster systems” 2003: 135-140.
  7. Fursov VA, Shustov VA, Skuratov SA. The technology of iterative resource allocation in a heterogeneous cluster. Proceedings of the All-Russian Scientific Conference “High-performance computing and their applications” 2000: 43-46.

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