Multiple Space Filter Design
1999 (English)In: Proceedings of the SSAB symposium on image analysis: Gothenburg, 1999Conference paper (Refereed)
This paper presents a general approach for obtaining optimal filters as well as filter sequences. A filter is termed optimal when it minimizes a chosen distance measure with respect to an ideal filter. The method allows specification of the metric via simultaneous weighting functions in multiple domains, e.g. the spatio-temporal space and the Fourier space. It is shown how convolution kernels for efficient spatio-temporal filtering can be implemented in practical situations. The method is based on applying a set of jointly optimized filter kernels in sequence. The optimization of sequential filters is performed using a novel recursive optimization technique. A number of optimization examples are given that demonstrate the role of key parameters such as: number of kernel coefficients, number of filters in sequence, spatio-temporal and Fourier space metrics. In multidimensional filtering applications the method potentially outperforms both standard convolution and FFT based approaches by two-digit numbers.
Place, publisher, year, edition, pages
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-21637OAI: oai:DiVA.org:liu-21637DiVA: diva2:242180