Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/8809
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dc.contributor葉家宏zh_TW
dc.contributorChia-Hung Yehen_US
dc.contributor.advisor張敏寬zh_TW
dc.contributor.advisorMin-Kuan Changen_US
dc.contributor.author蘇明政zh_TW
dc.contributor.authorSu, Ming-Chengen_US
dc.contributor.other中興大學zh_TW
dc.date2011zh_TW
dc.date.accessioned2014-06-06T06:42:09Z-
dc.date.available2014-06-06T06:42:09Z-
dc.identifierU0005-1205201016404300zh_TW
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Sethuraman, and R. Sarmiento, “Low-cost super-resolution algorithms implementation over a HW/SW video compression platform,” EURASIP Journal on Applied Signal Processing 2006 (2006) 1-29. [32] S. Chaudhuri and D. R. Taur, “High resolution slow motion sequencing,” IEEE Signal Processing Magazine 22 (2005) 16-24. [33] Y. Cheng, X. Fang, J. Hou, and S. Yu, “Multiframe super-resolution reconstruction based on cycle-spinning,” Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, 2007, pp. I-557-I-560. [34] L. Zhou, B. Zheng, A. Wei, B. Geller, and J. Cui, “A robust resolution-enhancement scheme for video transmission over mobile ad-hoc networks,” IEEE Trans. Broadcasting 54 (2008) 312-321. [35] R. Hardie, “A fast super-resolution algorithm using an adaptive wiener filter,” IEEE Trans. Image Process. 16 (2007) 2953-2964. [36] C.-T. Lin, K.-W. Fan, H.-C. Pu, S.-M. Lu, and S.-F. Liang, “An HVS-direction neural-network-based image resolution enhancement scheme for image resizing,” IEEE Trans. Fuzzy Systems 15 (2007) 605-615. [37] V. Bannore and L. Swierkowski, “Fast Iterative Super-Resolution for Image Sequences,” 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications, 2007, pp. 286-293.zh_TW
dc.identifier.urihttp://hdl.handle.net/11455/8809-
dc.description.abstract在本文中,我們提出了一個適應圖像放大方案基於反覆投射。初步估計每個放大圖像可以單獨創建的空間和時間域通過使用次像素插值和次像素運動估計。然後,根據初步估計和圖像內容,圖像重建方法利用一種改進的反覆投射技術,融合成一個放大的圖像。最後,低通濾波器作為一個後處理應用,以減少塊效應在重建高分辨率的圖像。我們的實驗結果是使用PSNR和NQM來評估影像的品質。zh_TW
dc.description.abstractIn this paper, we propose an adaptive image enlargement scheme based on iterative back-projection. Initial estimates of each enlarged image can be individually created from the spatial and temporal domains by using sub-pixel interpolation and sub-pixel motion estimation. Then, based on the initial estimates and image content, reconstructed images are derived by using a modified iterative back-projection technique and fused into a enlarged image. Finally, a low-pass filter as a post-processing is applied to reduce the blocking artifacts in the reconstructed high-resolution images. Our experiment results demonstrate that, in terms of PSNR and NQM, the proposed scheme is superior to existing methods.en_US
dc.description.tableofcontents1. Introduction...1 2. System description...5 A. Problem formulation...5 B. Architecture of proposed scheme...6 3. The Proposed Image Enlargement Scheme...9 A. Image registration and initialization...9 B. Modified iterative back-projection algorithm...11 B.1 Basic structure...12 B.2 Detailed compensation rule...14 C. Image fusion and post-processing...17 4. Experiment Results...18 A. Performance evaluation...19 B. Comparison with [12] and [37]...23 3. Conclusion...38 3. References...39en_US
dc.language.isoen_USzh_TW
dc.publisher電機工程學系所zh_TW
dc.relation.urihttp://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-1205201016404300en_US
dc.subjectresolution enhancementen_US
dc.subject像素增強zh_TW
dc.subjectsuper-resolutionen_US
dc.subjectiterative back projectionen_US
dc.subject超解析zh_TW
dc.subject反覆投射zh_TW
dc.title基於反覆投射與次像素移動估計之視訊解析度增強技術zh_TW
dc.titleVideo resolution enhancement technique based on iterative back-projection and sub-pixel motion estimationen_US
dc.typeThesis and Dissertationzh_TW
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeThesis and Dissertation-
item.cerifentitytypePublications-
item.fulltextno fulltext-
item.languageiso639-1en_US-
item.grantfulltextnone-
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