Sieves and wavelets: multiscale transforms for pattern recognition

JA Bangham, TG Campbell

Research output: Contribution to conferenceOther


In this paper a scalelposition decomposition that is an alternative to wavelets is described. The nonlinear decomposition, called the datasieve, is appropriate for isolating and locating the position of objects with sharp edges arising from nonlinear events such as occlusion. It can represent structural information in a way that is independent of spatial frequency, has different uncertainty tradeoffs, and can be used for scale, position and contrast independent pattern recognition.
Original languageEnglish
Number of pages6
Publication statusPublished - 1993
EventIEEE Winter Workshop on Nonlinear Digital Signal Processing -
Duration: 17 Jan 199320 Jan 1993


ConferenceIEEE Winter Workshop on Nonlinear Digital Signal Processing

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