Local adaptive filtering in transform domain for image restoration, enhancement and target location

L. Yaroslavsky*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

10 Scopus citations


Local adaptive linear filters for image restoration were reported by the present author on one of the previous Wien workshops on image processing and computer graphics (1). The filters work in the domain of an orthogonal transform (specifically, in the domain of DFT or DCT transforms) in a moving window and nonlinearly modify the transform coefficients to obtain an estimate of the central pixel of the window. In the present paper, we suggest an extension of local adaptive filtering in the domain of DFT/DCT to the processing multicomponent (i.e., color) images, describe a recursive algorithm for local 3-D DCT spectrum analysis which permits to substantially reduce the computational complexity of the filtering, present experimental results in denoising, enhancement and deblurring monochrome and color images and in target location in stereoscopic images. We also discuss using other than DCT orthogonal transforms such as Walsh-Hadamard and Haar transforms and show that, for the window size 3 × 3 pixels, filtering in transform domain can be carried out in a form of 5 channel convolution with masks implementing local mean and 4 directional Laplacians: horizontal, vertical and two (±45°) diagonal.

Original languageEnglish
Pages (from-to)2-17
Number of pages16
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 1997
Event6th International Workshop on Digital Image Processing and Computer Graphics (DIP-97): Applications in Humanities and Natural Sciences - Vienna, Austria
Duration: 20 Oct 199722 Oct 1997


  • Adaptive filters
  • Image enhancement
  • Image restoration
  • Target location
  • Transforms


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