研究生: |
鄭仁舜 Jen-Shun Cheng |
---|---|
論文名稱: |
使用多重線性回歸技術針對RGB全彩影像之有效 彩度抽樣和亮度修正 Effective Chroma Subsampling and Luma Modidication for RGB Full-color Images Using the Multiple Linear Regression Technique |
指導教授: |
鍾國亮
Kuo-Liang Chung |
口試委員: |
貝蘇章
Soo-Chang Pei 廖弘源 Hong-Yuan Liao 范國清 Kuo-Chin Fan 花凱龍 Kai-Lung Hua |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 資訊工程系 Department of Computer Science and Information Engineering |
論文出版年: | 2020 |
畢業學年度: | 108 |
語文別: | 英文 |
論文頁數: | 39 |
中文關鍵詞: | 彩度抽樣 、失真模型 、亮度修正 、多元線性回歸 、品質位元 率權衡 、RGB全彩影像 、通用視頻編碼 |
外文關鍵詞: | Chroma subsampling, Distortion model, Luma modification, Multiple linear regression, Quality-bitrate tradeoff, RGB full-color image, Versatile video coding (VVC) |
相關次數: | 點閱:220 下載:0 |
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與傳統 RGB 全彩影像轉成 YUV 的彩度抽樣方法不同,本文提出 了一種新穎有效的彩度抽樣和亮度修正(CSLM)方法。對於每個 2×2 YUV區塊,首先,提出了一個新的重建 2×2 RGB 全彩色塊失真模型,然後為了使重建的 2×2 RGB 全彩色塊可以最大程度地減少色塊失真,我們提出了一種多元線性回歸方法來解我們的 CSLM 方法,從而顯著改善 重構的 RGB 全採影像的品質。綜合實驗結果顯示,我們的方法在通用視頻編碼(VVC)針對重建RGB全彩影像,相對於六種傳統方法和三種最 新方法比較,具有更好的品質和品質位元率權衡優勢。
Differing from the traditional chroma subsampling on the YUV image converted from a RGB full-color image, in this thesis, we propose a novel and effective chroma subsampling and luma modification (CSLM) method. For each 2x2 YUV block, first, a newly reconstructed 2x2 RGB full-color block-distortion model is proposed, and then we propose a multiple linear regression approach to tackle our CSLM method such that the reconstructed 2x2 RGB full-color block-distortion can be minimized, achieving significant quality improvement of the reconstructed RGB full-color image. Based on the Kodak and IMAX datasets, the comprehensive experimental results demonstrated that on the versatile video coding (VVC) platform VTM-8.0, our method achieves substantial quality and quality-bitrate tradeoff improvement of the reconstructed RGB full-color images relative to six traditional methods and the three state-of-the-art methods.
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