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dc.contributor.authorNowak, Robert David
Baraniuk, Richard G.
dc.creatorNowak, Robert David
Baraniuk, Richard G.
dc.date.accessioned 2007-10-31T00:56:04Z
dc.date.available 2007-10-31T00:56:04Z
dc.date.issued 1996-04-01
dc.date.submitted 1996-04-01
dc.identifier.citation R. D. Nowak and R. G. Baraniuk, "Optimally Weighted Highpass Filters using Multiscale Analysis," 1996.
dc.identifier.urihttps://hdl.handle.net/1911/20154
dc.description Conference Paper
dc.description.abstract An obvious approach to image enhancement is to sharpen bright regions of an image more than darker regions. One very simple method to accomplish this is to weight the amount of highpass filtering proportional to the local mean. This gives rise to a class of nonlinear image enhancement filters known as mean-weighted highpass filters. We propose a general framework for studying a class of weighted highpass filters. Our framework, based on a multiscale signal decomposition, allows us to study a wide class of filters and to assess the merits of each. We derive an automatic procedure to optimally tune a filter to the local structure of the image under consideration. The entire algorithm is fully automatic and requires no parameter specification from the user. Several simulations demonstrate the efficacy of the proposed algorithm.
dc.language.iso eng
dc.subject.otherDSP for Communications
dc.title Optimally Weighted Highpass Filters using Multiscale Analysis
dc.type Conference paper
dc.date.note 2006-06-12
dc.citation.bibtexName inproceedings
dc.date.modified 2006-06-12
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)
dc.citation.location San Antonio, TX
dc.citation.conferenceName IEEE Southwest Symposium on Image Analysis and Interpretation
dc.type.dcmi Text
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1109/IAI.1996.493757
dc.citation.firstpage 224
dc.citation.lastpage 229


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  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.
  • ECE Publications [1287]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students

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