適用於鬆散光場應用之基於區塊切割之快速擬真事後對焦演算法設計

光場相機的發明可謂顛覆了傳統相機的攝影模式。拍完照後再事後對焦的特性，已然成為一種取得含淺景深影像的新趨勢。近年來，利用光場來做事後對焦的相關研究中，仍未能達到同時保有高畫質擬真的影像與即時生成的技術，所以對於此方面的研究在此應用的推廣上則顯得十分重要。　　本論文將提出以區塊切割的架構來設計應用於鬆散光場的事後對焦演算法。使用鬆散光場有效的減少了相對於緊密光場所需的資料儲存量，同時也提高了影像的解析度。利用區塊切割影像的特性，可針對不同的區塊採取不同的演算法。而以四元樹的區塊切割模式下，將會利用運算複雜度的分析來預測區塊的運算時間，並以較少運算時間為基準來決定區塊間是否合併。我們提出一個金字塔結構的光場來做多層級的事後對焦，進而降低運算複雜度，而達到加速的目的。然而以區塊切割方式直接重新對焦將會產生嚴重的區塊效應，為了解決此一問題，我們提出了一個快速的邊界範圍選取方法，減少多抓邊界後再事後對焦所產生多餘的運算量。　　最後，我們會使用不同解析度的光場來對我們的演算法做測試。實驗裡，我們發現對於場景其深度資訊的不同，加速的程度會有所不同，而最快可達到約二十一倍的加速。結果顯示影像的品質並沒有明顯的降低，但時間運算量確實被大量地減少。

關鍵字

事後對焦；光場

並列摘要

In recent years, the revolution in computational photography has appeared with the invention of light field cameras. The specific ability of changing the focal planes after the light field is captured enables users to edit their shallow-depth-of-field pictures at any time. Despite the fact that many research works achieved advanced improvement on light-field processing, high-resolution and realistic refocusing is still a challenge. Therefore, it is an essential issue to resolve for enabling high-quality light-field video applications. In this thesis, we propose a block-based processing structure for refocusing for sparse light fields. Using sparse light fields effectively reduces the storage requirement and achieves higher image resolution compared to dense light fields. We devise a timing-based block merging algorithm to achieve the best quadtree partition in terms of computation time. Also, we implement a multi-level pyramid refocusing scheme to reduce the unnecessary computation, especially for the blocks with heavily defocused blurs. However, overlapped blocks are required to eliminate the block effect, and we proposed a fast block-border search method to select the boundaries efficiently. Finally, we apply our algorithm to many light fields which are from different sources and have different characteristics. In our experiment, we show that the speedup performance is scene-dependent and can be up to 21x without visible quality degradation.

並列關鍵字

refocus ； light field

參考文獻

[1] M. Levoy, “Light fields and computational imaging,” IEEE Computer, 2006, pp. 46-55.

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[8] Yuichi Taguchi, Amit Agrawal, Ashok Veeraraghavan, Srikumar Ramalingam, and Ramesh Raskar, “Axial-cones: Modeling spherical catadioptric cameras for wide-angle light field rendering,” ACM Trans. Graph., vol. 29, no. 6, pp. 172:1–172:8, Dec. 2010.

[9] F. Moreno-Noguer, P.N. Belhumeur, and S.K. Nayar, “Active refocusing of images and videos,” ACM Trans. Graph., Aug 2007.

[10] Benjamin Huhle, Timo Schairer, Philipp Jenke, and Wolfgang Strasser, “Realistic depth blur for images with range data,” in Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging, 2009, pp. 84–95.

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適用於鬆散光場應用之基於區塊切割之快速擬真事後對焦演算法設計

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