運用高頻資訊補償之超解析度演算法研究

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張書梵(Shu-Fan Chang) 查詢紙本館藏

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通訊工程學系

論文名稱

運用高頻資訊補償之超解析度演算法研究
(High Frequency Compensated Super-Resolution Algorithm)

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摘要(中)

時至現今，已有許多重建高解析度影像的方法。這些方法主要是去除影像經內插放大時的模糊效應和適當的增加空間上的資訊，以還原其高解析度的面貌。在本研究的方法中，藉由迭代反投影法(Iterative Back Projection, IBP)的原理，並加入高頻補償模型，依據應用的不同，發展出直接高頻補償(Direct High Frequency Compensated, DHFC)和估測高頻補償(Estimated High Frequency Compensated, EHFC)兩種方法。
本論文所提的方法，除了大幅改善零次，雙線性，和三次立方等，傳統內插法所放大的影像品質外，主要在於改善IBP演算法的缺點。在一般影像測試的情形下，DHFC方法可提升約1~5.7倍的速度，並提升最終PSNR值約0.1~0.3dB；EHFC方法可提升約1~6.5倍的速度，並提升最終PSNR值約0.4~0.7dB。在文字影像測試的情形下，EHFC方法可提升約1~6.5倍的速度，並提升最終PSNR值約1.2~8.3dB。

摘要(英)

Currently, there exist many high resolution image reconstruction methods. The approach of these methods is mainly to remove the blur effect of image by interpolation enlargement and appropriately to increase the space information to restore its high resolution images. In this study, two methods, the Direct High Frequency Compensated (DHFC) and the Estimated High Frequency Compensated (EHFC), are developed based on the Iterative Back Projection (IBP) principle as well as the High Frequency Compensated Model. These methods substantially improve the image quality of reconstructed images enlarged by zero, bilinear, and bi-cubic interpolations. In addition, they accelerate the process significantly compared to IBP algorithm. In natural imaging test situation, DHFC method can increase the speed by 1~5.7 times and improve the ultimate PSNR value by 0.1~0.3dB while EHFC method can increase the speed by 1~6.5 times and improve the ultimate PSNR value by 0.4~0.7dB. Moreover, in text imaging test cases, EHFC method can increase the speed by 1~6.5 times and improve the ultimate PSNR value by 1.2~8.3dB.

關鍵字(中)

★ 影像重建
★ 超解析度
★ 反投影迭代
★ 影像內插
★ 高解析度

關鍵字(英)

★ image interpolation
★ image reconstruction
★ super-resolution
★ high-resolution
★ Iterative Back Projection

論文目次

摘要 I
目錄 III
圖目 V
表目 VII
第一章緒論 1
1.1 簡介 1
1.2 研究動機 4
1.3 論文架構 7
第二章超解析度影像重建技術之發展現況 9
2.1 研究議題與方向 9
2.2 觀察模型(影像退化模型) 10
2.3 文獻回顧 12
第三章影像內插法與相關投影迭代SR技術介紹 17
3.1 影像放大 17
3.2 傳統影像內插法簡介 21
3.2.1最鄰近像素內插法 21
3.2.2雙線性內插法 23
3.2.3雙立方內插法 25
3.3 邊緣保留影像內插法 27
3.4 投影迭代式超解析度演算法 29
3.4.1凸集合投影迭代法 29
3.4.2反投影迭代法 31
第四章運用高頻資訊補償之超解析度影像重建技術 35
4.1高頻重建修正概念介紹 36
4.2高頻補償SR演算法 44
4.2.1直接高頻補償法 44
4.2.2估測高頻補償法 51
4.3視訊高解析度重建機制 54
4.3.1移動補償與移動估測 54
4.3.2快速高解度視訊影像重建法 59
第五章實驗結果與討論 63
5.1實驗環境 63
5.1.1實驗軟硬體 63
5.1.2實驗影像樣本 63
5.1.3實驗影像退化程序 64
5.1.4效能比較方式 65
5.2靜態影像超解析度實驗結果與討論 66
5.2.1實驗結果 66
5.2.2討論 78
5.3動態影像超解析度實驗結果與討論 83
5.3.1實驗結果 84
5.3.2討論 85
第五章結論與未來展望 87
參考文獻 89

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指導教授

張寶基(Pao-Chi Chang)

審核日期

2008-1-18

推文