Efficient Computation of Convolution of Huge Images

  • David Svoboda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6978)

Abstract

In image processing, convolution is a frequently used operation. It is an important tool for performing basic image enhancement as well as sophisticated analysis. Naturally, due to its necessity and still continually increasing size of processed image data there is a great demand for its efficient implementation. The fact is that the slowest algorithms (that cannot be practically used) implementing the convolution are capable of handling the data of arbitrary dimension and size. On the other hand, the fastest algorithms have huge memory requirements and hence impose image size limits. Regarding the convolution of huge images, which might be the subtask of some more sophisticated algorithm, fast and correct solution is essential. In this paper, we propose a fast algorithm implementing exact computation of the shift invariant convolution over huge multi-dimensional image data.

Keywords

Convolution Fast Fourier Transform Divide-et-Impera 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • David Svoboda
    • 1
  1. 1.Centre for Biomedical Image Analysis, Faculty of InformaticsMasaryk UniversityBrnoCzech Republic

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