Accelerating the Distribution Estimation for the Weighted Median/Mode Filters
Refereed conference paper presented and published in conference proceedings

香港中文大學研究人員

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其它資訊
摘要Various image filters for applications in the area of computer vision require the properties of the local statistics of the input image, which are always defined by the local distribution or histogram. But the huge expense of computing the distribution hampers the popularity of these filters in real-time or interactive-rate systems. In this paper, we present an efficient and practical method to estimate the local weighted distribution for the weighted median/mode filters based on the kernel density estimation with a new separable kernel defined by a weighted combinations of a series of probabilistic generative models. It reduces the large number of filtering operations in previous constant time algorithms [1,2] to a small amount, which is also adaptive to the structure of the input image. The proposed accelerated weighted median/mode filters are effective and efficient for a variety of applications, which have comparable performance against the current state-of-the-art counterparts and cost only a fraction of their execution time.
著者Sheng L, Ngan KN, Hui TW
會議名稱12th Asian Conference on Computer Vision (ACCV)
會議開始日01.11.2014
會議完結日05.11.2014
會議地點Singapore
會議國家/地區新加坡
期刊名稱Lecture Notes in Artificial Intelligence
詳細描述organized by Asian Federation of Computer Vision Societies,
出版年份2015
月份1
日期1
卷號9006
出版社SPRINGER-VERLAG BERLIN
頁次3 - 17
國際標準書號978-3-319-16816-6
電子國際標準書號978-3-319-16817-3
國際標準期刊號0302-9743
語言英式英語
Web of Science 學科類別Computer Science; Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Theory & Methods; Medical Informatics; Robotics

上次更新時間 2020-27-11 於 01:27