教師資料查詢 | 類別: 期刊論文 | 教師: 周建興 Chien-hsing Chou (瀏覽個人網頁)

標題:A Reinforcement-Learning Approach to Color Quantization
學年99
學期2
出版(發表)日期2011/06/01
作品名稱A Reinforcement-Learning Approach to Color Quantization
作品名稱(其他語言)
著者Chou, Chien-Hsing; Su, Mu-Chun; Zhao, Yu-Xiang; Hsu, Fu-Hau
單位淡江大學電機工程學系
出版者新北市淡江大學
著錄名稱、卷期、頁數Tamkang Journal of Science and Engineering=淡江理工學刊 14(2), pp.141-150
摘要Color quantization is a process of sampling three-dimensional color space (e.g. RGB) to reduce the number of colors in a color image. By reducing to a discrete subset of colors known as a color codebook or palette, each pixel in the original image is mapped to an entry according to these palette colors. In this paper, a reinforcement-learning approach to color image quantization is proposed. Fuzzy rules, which are used to select appropriate parameters for the adaptive clustering algorithm applied to color quantization, are built through reinforcement learning. By comparing this new method with the original adaptive clustering algorithm on 30 color images, our method shows an improvement of 3.3% to 5.8% in peak signal to noise ratio (PSNR) values on average and results in savings of about 10% in computation time. Moreover, we demonstrate that reinforcement learning is an efficacious as well as efficient way to provide a solution of the learning problem where there is a lack of knowledge regarding the input-output relationship.
關鍵字
語言英文
ISSN1560-6686
期刊性質國外
收錄於EI;
產學合作
通訊作者Chou, Chien-Hsing
審稿制度
國別中華民國
公開徵稿
出版型式,紙本
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