Summary
Local adaptive filters for image restoration (denoising and deblurring), enhancement and target location are described. The filters work in the domain of an orthogonal transform (DFT, DCT or other transforms) in a moving window and nonlinearly modify the transform coefficients to obtain an estimate of the central pixel of the window. A framework for the filter design for multi-component images is presented and experimental results in denoising, enhancement and deblurring monochrome and color images, and in target location are provided. Also discussed is the filter implementation for a window size of 3 × 3 pixels in the form of five-channel convolution with masks implementing the local mean and four directional Laplacians: horizontal, vertical, and two (±45°) diagonal ones.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gabor, D. (1946) Theory of Communication. J Inst Elec Eng 93: 429–457
Yaroslaysky, L. (1987) Digital signal processing in optics and holography. Radio i Svyaz, Moscow (in Russian)
Vitkus, R.Yu., Yaroslaysky, L.P. (1988) Adaptive Linear Filters for Image Processing. In: Siforov, V.I., Yaroslaysky, L.P. (Eds.) Adaptive Methods for Image Processing. Nauka, Moscow, pp 6–35 (in Russian)
Yaroslaysky, L.P. (1991) Linear and Rank Adaptive Filters for Image Processing. In: Dimitrov, L., Wenger, E. (Eds.) Digital Image Processing and Computer Graphics. Theory and Applications. Oldenburg, Wien München, p 374
Yaroslaysky, L.P. (1996) Local Adaptive Filters for Image Restoration and Enhancement. In: Berger, M.-O., Deriche, R., Herlin, I., Jaffre, J., Morel, J.-M. (Eds.) 12th Int. Conf. on Analysis and Optimization of Systems. Images, Wavelets and PDE’s, Paris, June 26–28. Lecture Notes in Control and Information Sciences, 219. Springer-Verlag, Heidelberg, pp 31–39
Yaroslaysky, L. (1996) Local Adaptive Image Restoration and Enhancement with the Use of DFT and DCT in a Running Window. In: Unser, A., Aldroubi, A., Laine, A.F. (Eds.) Wavelet Applications in Signal and Image Processing IV, SPIE Vol. 2825, pp 2–11
Yaroslaysky, L., Eden, M. (1996) Fundamentals of Digital Optics. Birkhauser, Boston
Yaroslaysky, L.P. (1993) The Theory of Optimal Methods for Localization of Objects in Pictures. In: Wolf, E. (Ed.) Progress in Optics, Vol. XXXII. Elsevier, Amsterdam
Yaroslaysky, L. (1997) Nonlinear Adaptive Image Processing in Transform Domain. In: IEEE Workshop on Nonlinear Signal and Image Processing, Sept. 7–11, Mckinac Island, Michigan
Yaroslaysky, L., Marom, E. (1997) Nonlinearity Optimization in Nonlinear Joint Transform Correlators. Appl Optics 36 (July): 1–7
Vitkus, R.Y., Yaroslaysky, L.P. (1987) Recursive Algorithms for Local Adaptive Linear Filtration. In: Yaroslayskii, L.P., Rosenfeld, A., Wilhelmi, W. (Eds.) Mathematical Research. Academie Verlag, Berlin, pp 34–39
Pratt, W.K. (1978) Digital Image Processing. Wiley, New York
Donoho, D.L., Johnstone, I.M. (1994) Ideal spatial adaptation by wavelet shrinkage. Biometrica 81 (3): 425–455
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Yaroslavsky, L. (1999). Image Restoration, Enhancement and Target Location with Local Adaptive Linear Filters. In: Asakura, T. (eds) International Trends in Optics and Photonics. Springer Series in OPTICAL SCIENCES, vol 74. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48886-6_9
Download citation
DOI: https://doi.org/10.1007/978-3-540-48886-6_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-14212-7
Online ISBN: 978-3-540-48886-6
eBook Packages: Springer Book Archive