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Binocular tone mapping. / 雙目色調映射 / CUHK electronic theses & dissertations collection / Shuang mu se diao ying she

隨著3D電影和遊戲的蓬勃發展,雙目(立體)顯示設備日益流行,也變得更為廉價。 立體顯示設備 引入了一個額外的圖像空間,使得用於顯示的圖像域翻倍(一個圖像域對應左眼,另一個對應右眼)。 目前的雙目(立體)顯示設備主要把這個額外的圖像空間用於顯示三維立體信息。 / 人們的雙目視覺系統不僅可以把雙眼看到的具有深度差異信息的兩個圖像融合起來,而且可以把兩個在亮度,色彩, 對比度,甚至是內容細節上有一定程度不同的圖像融合到一起,形成一個單一的視界。 這個現象叫做雙眼單視界(Binocular Single Vision)。通過一些列複雜的神經生理融合過成,人們可以通過雙眼單視界比只用任意一隻單眼 觀察到更多視覺內容和信息,其獲得的信息量也多於兩個視野的線性組合。 / 在本畢業論文中,雙眼單視界首次被應用到了計算機圖形學領域,基於這一現象,提出了一個新穎的雙目色調映射框架(Binocular Tone Mapping Framework)。對於輸入的高動態範圍(High-Dynamic Range, HDR)圖像,我們的雙目色調映射 構架將生成一組用於雙目觀看的低動態範圍(Low-Dynamic Range, LDR)圖像對,用以從原HDR圖像中保留 更多的人們可感知到的視覺內容和信息。 給定任意一個指定的色調映射方法,我們的雙目計算框架首先通過使用其默認或者 人工選擇的參數生成一張LDR圖像(不失一般性,我們指定為左視野圖),隨後,圖像對中的另一張LDR圖像 將由系統從同一HDR圖像源使用最優化算法生成。 結果的兩張LDR圖像是不相同的,它們分別保留了不同的視覺信息。通過使用雙目顯示設備,它們可以合計表現出比任一單張LDR圖像更豐富的圖像內容。 / 人們的兩個視野對圖像差異不是無限的,也存在一個容忍度。一旦超過了某個限制閾值,視覺上的不適感覺就會出現。 了避免不適 的產生,我們設計了一個全新的雙目視覺舒適預測預器(Binocular Viewing Comfort predictor)用以預測 雙目視覺的不舒適閾值。 在我們的雙目色調映射構架中,BVCP用於指導LDR圖像對的生成,同時避免觸發 任何視覺不適。 通過一些列的實驗和用戶調查,我們提出的工作框架的有效性以及BVCP預測不適閾值的準確程度都得到了驗證。 / With the booming of 3D movies and video games, binocular (stereo) display devices become more and more popular and affordable. By introducing one additional image space, stereo displays double the image domains for visualization, one for the left eye and the other for the right eye. Existing binocular display systems only utilize this dual image domain for stereopsis. / Our human binocular vision is not only able to fuse two images with disparity, but also two images with difference in luminance, contrast and even detail, into a single percept, up to a certain limit. This phenomenon is known as binocular single vision. By a complicated neurophysiologic fusion process, humans can perceive more visual content via binocular single vision than one arbitrary single view or the linear blending of two views. / In this thesis, for the first time, binocular single vision has been utilized into computer graphics. Based on this phenomenon, a novel binocular tone mapping framework is proposed. From the source high-dynamic range (HDR) image, the proposed framework generates a binoc- ular low-dynamic range (LDR) image pair that preserves more human- perceivable visual content than a single LDR image using the additional image domain. Given a tone mapping method, our framework firstly generates one tone-mapped LDR image (left, without loss of generality) by the default or user selected parameters. Then its counterpart image (right) of the LDR pair is optimally synthesized from the same source HDR image. The two LDR images are not identical, and contain different visual information. Via binocular displays, they can aggregately present more human-perceivable visual richness than a single arbitrary LDR image. / Human binocular vision has a tolerance on the difference between two views. When such limit is exceeded, binocular viewing discomfort appears. To prevent such visual discomfort, a novel binocular view- ing comfort predictor (BVCP) is also proposed to predict the comfort threshold of binocular vision. In our framework, BVCP is used to guide the generation of LDR image pair without triggering visual discomfort. Through several user studies, the effectiveness of the proposed framework in increasing human-perceivable visual richness and the pre- dictability of the proposed BVCP in predicting the binocular discomfort threshold have been demonstrated and validated. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Yang, Xuan. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 108-115). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.ix / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background Study --- p.5 / Chapter 2.1 --- Stereo Display --- p.5 / Chapter 2.2 --- HDR Tone Mapping --- p.9 / Chapter 2.2.1 --- HDR lmage --- p.9 / Chapter 2.2.2 --- Tone Mapping --- p.11 / Chapter 3 --- Binocular Vision --- p.16 / Chapter 3.1 --- Binocular Single Vision --- p.16 / Chapter 3.1.1 --- Binocular Single Vision --- p.16 / Chapter 3.1.2 --- Motor Fusion and Sensory Fusion --- p.19 / Chapter 3.1.3 --- Fusion, Suppression and Rivalry --- p.21 / Chapter 3.1.4 --- Rivalry --- p.23 / Chapter 3.1.5 --- Fusional Theory --- p.24 / Chapter 3.1.6 --- Fusion with Stereopsis --- p.27 / Chapter 3.2 --- Binocular discomfort --- p.29 / Chapter 3.2.1 --- Fusional area --- p.31 / Chapter 3.2.2 --- Contour difference --- p.32 / Chapter 3.2.3 --- Failure of rivalry --- p.33 / Chapter 3.2.4 --- Contour and regional contrast --- p.34 / Chapter 4 --- Binocular Visual Comfort Predictor (BVCP) --- p.37 / Chapter 4.1 --- Introduction --- p.37 / Chapter 4.2 --- Design of BVCP --- p.40 / Chapter 4.2.1 --- Fusional Area --- p.40 / Chapter 4.2.2 --- Contour Fusion --- p.42 / Chapter 4.2.3 --- Failure of Rivalry --- p.48 / Chapter 4.2.4 --- Contour and Regional Contrast --- p.53 / Chapter 4.2.5 --- The Overall Fusion Predictor --- p.54 / Chapter 4.3 --- Experiments and User Study --- p.56 / Chapter 4.4 --- Discussion --- p.60 / Chapter 5 --- Binocular Tone Mapping --- p.62 / Chapter 5.1 --- Introduction --- p.62 / Chapter 5.2 --- Binocular Tone Mapping Framework --- p.66 / Chapter 5.2.1 --- System Overview --- p.66 / Chapter 5.2.2 --- Optimization --- p.68 / Chapter 5.3 --- Experiments and Results --- p.71 / Chapter 5.4 --- Userstudy --- p.77 / Chapter 5.4.1 --- Visual Richness --- p.77 / Chapter 5.4.2 --- Binocular Symmetry --- p.81 / Chapter 5.5 --- Discussion --- p.82 / Chapter 5.5.1 --- Incorporating Stereopsis --- p.82 / Chapter 5.5.2 --- Limitation --- p.84 / Chapter 5.5.3 --- Extension --- p.85 / Chapter 6 --- Conclusion --- p.91 / Chapter 6.1 --- Contribution --- p.91 / Chapter 6.2 --- Future Work --- p.92 / Chapter A --- More Results of Binocular Tone Mapping --- p.94 / Chapter B --- Test Sequence for BVCP --- p.103 / Bibliography --- p.108

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_328044
Date January 2012
ContributorsYang, Xuan, Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatelectronic resource, electronic resource, remote, 1 online resource (xxii, 115 leaves) : ill. (chiefly col.)
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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