NDLI: Fast Almost-Gaussian Filtering

Content Provider	IEEE Xplore Digital Library
Author	Kovesi, P.
Copyright Year	2010
Abstract	Image averaging can be performed very efficiently using either separable moving average filters or by using summed area tables, also known as integral images. Both these methods allow averaging to be performed at a small fixed cost per pixel, independent of the averaging filter size. Repeated filtering with averaging filters can be used to approximate Gaussian filtering. Thus a good approximation to Gaussian filtering can be achieved at a fixed cost per pixel independent of filter size. This paper describes how to determine the averaging filters that one needs to approximate a Gaussian with a specified standard deviation. The design of bandpass filters from the difference of Gaussians is also analysed. It is shown that difference of Gaussian bandpass filters share some of the attributes of log-Gabor filters in that they have a relatively symmetric transfer function when viewed on a logarithmic frequency scale and can be constructed with large bandwidths.
Starting Page	121
Ending Page	125
File Size	440430
Page Count	5
File Format	PDF
ISBN	9781424488162
DOI	10.1109/DICTA.2010.30
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-01
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision Gaussian smoothing Laplace equations Transfer functions Bandwidth Difference of Gaussian filtering Approximation methods Pixel Frequency domain analysis
Content Type	Text
Resource Type	Article

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