Abstract
In image contrast enhancement [2, 4, 5], quadratic and more generally polynomial filters are a very popular class of nonlinear filters. These filters exhibit good performances in terms of visual quality, but present some drawbacks such as the elimination of usefull information when using a fixed filter. In this paper we propose a new family of adaptive quadratic filters, where a weighted filter mask is adaptively determined according to the minimization of a prediction error. This filter is then used to enhance locally the image contrast. The results we proposed point out the improvement provided by these new filters in comparison with recent approaches [4, 2].
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.