Paper
10 November 2004 Design of a new sharpening filter
Georgios Aim. Skianis, Dimitrios A. Vaiopoulos, Konstantinos G. Nikolakopoulos
Author Affiliations +
Proceedings Volume 5573, Image and Signal Processing for Remote Sensing X; (2004) https://doi.org/10.1117/12.565730
Event: Remote Sensing, 2004, Maspalomas, Canary Islands, Spain
Abstract
In the present paper is designed a new sharpening filter, whose response is controlled by two characteristic positive parameters b and k. Using the Fourier transform, it is studied the effect of this filter on two-dimensional signals of radial symmetry. It is observed that certain deformations may be produced, if the signal has the shape of a rapidly changing pulse. These deformations are more obvious for small b values. If the signal is smooth (gaussian type), no deformations are observed. Convolution masks are then constructed at the image domain, which simulate the filter response at frequency domain. The masks are applied on a satellite image and their effect is compared to that of other frequently used sharpening filters. It is observed that for proper b and k values the proposed filter produces images with an enhanced tonality contrast and with no high frequency noise. The general conclusion is that the proposed filter is successful in enhancing tonality differences between adjacent pixels. For different values of the parameters k and b, different tonality contrasts may be obtained. The potential user is encouraged to try on various k and b values, in order to obtain the optimum result for the area under study.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Georgios Aim. Skianis, Dimitrios A. Vaiopoulos, and Konstantinos G. Nikolakopoulos "Design of a new sharpening filter", Proc. SPIE 5573, Image and Signal Processing for Remote Sensing X, (10 November 2004); https://doi.org/10.1117/12.565730
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KEYWORDS
Image filtering

Convolution

Electronic filtering

Image enhancement

Filtering (signal processing)

Fourier transforms

Gaussian filters

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