An Image Compression Method Based on Block Truncation Coding and Linear Regression

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題名:	An Image Compression Method Based on Block Truncation Coding and Linear Regression
作者:	CHang；, Wan-Li Lyu；Wan-Li Lyu；張真誠；Chin-Chen
貢獻者:	資訊工程學系
日期:	2016-01
上傳時間:	2016-09-20 03:43:38 (UTC+0)
摘要:	This paper describes an image compression method based on block truncation coding (BTC) and linear regression coding (LRC) hybrid strategy. BTC is simple and easy to use, but only two representative values can not adequately represent the visual feature of image blocks. However, LRC can obtain different values of points with the line function by recording the coefficient of the regression line while the data distribution shows a linear relationship. The proposed method designs a hybrid strategy to combine the advantages of the two methods to improve image quality. In the paper, first, models are designed to rearrange the data of image blocks to satisfy a linear distribution, and then these models are used to code the image blocks. The experimental results indicated that the proposed method is superior to the BTC scheme in terms of image quality, and it can be used for image compression applications.
關聯:	Journal of Information Hiding and Multimedia Signal Processing
顯示於類別:	[資訊工程學系] 期刊論文

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