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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳家麟 | |
| dc.contributor.author | Yu-Hsun Lin | en |
| dc.contributor.author | 林裕訓 | zh_TW |
| dc.date.accessioned | 2021-06-16T05:51:47Z | - |
| dc.date.available | 2014-08-12 | |
| dc.date.copyright | 2014-08-12 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-08-08 | |
| dc.identifier.citation | [1] Final Report From The Video Quality Experts Group On The Validation Of Objective Models Of Video Quality Assessment. VQEG, Jun. 2000.
[2] Report on Experimental Framework for 3D Video Coding. ISO/IEC JTC1/SC29/WG11 MPEG2010/N11631, Oct. 2010. [3] Call for Proposals on 3D Video Coding Technology. ISO/IEC JTC1/SC29/WG11 MPEG2011/N12036, Mar. 2011. [4] Common Test Conditions for HEVC- and AVC-based 3DV. ISO/IEC JTC1/SC29/WG11 MPEG2011/N12352, Dec. 2011. [5] Methodology for the subjective assessment of the quality of television pictures. ITU Recommendation BT.500-13, Jan. 2012. [6] Subjective methods for the assessment of stereoscopic 3DTV systems. Draft new Recommendation ITU-R BT.2021, May 2012. [7] P. Aflaki, M. Hannuksela, J. Ha andkkinen, P. Lindroos, and M. Gabbouj. Subjective study on compressed asymmetric stereoscopic video. IEEE ICIP 2010, pages 4021–4024, Sep. 2010. [8] R. Akhter, Z. M. Parvez Sazzad, Y. Horita, and J. Baltes. No-reference stereoscopic image quality assessment. Proc. SPIE, Stereoscopic Displays and Applications XXI, 7524:75240T–1–75240T–12, 2010. [9] D. H. Baker and T. S. Meese. Binocular contrast interactions: Dichoptic masking is not a single process. Vision Research, 47(24):3096–3107, 2007. [10] D. H. Baker, S. A. Wallis, M. A. Georgeson, and T. S. Meese. Nonlinearities in the binocular combination of luminance and contrast. Vision Research, 56(0):1–9, 2012. [11] A. Benoit, P. L. Callet, P. Campisi, and R. Cousseau. Quality assessment of stereoscopic images. EURASIP Journal on Image and Video Processing, 2008(659024):1–13, 2008 (2009). [12] R. Bensalma and M.-C. Larabi. A perceptual metric for stereoscopic image quality assessment based on the binocular energy. Multidimensional Systems and Signal Processing, 24(2):281–316, 2013. [13] R. Blake and H. Wilson. Binocular vision. Vision Research, 51(7):754–770, 2011. [14] D. Chandler and S. Hemami. Vsnr: A wavelet-based visual signal-to-noise ratio for natural images. IEEE Trans. on Image Processing, 16(9):2284–2298, Sep. 2007. [15] M.-J. Chen, L. Cormack, and A. Bovik. No-reference quality assessment of natural stereopairs. IEEE Transactions on Image Processing, 22(9):3379–3391, 2013. [16] M.-J. Chen, C.-C. Su, D.-K. Kwon, L. K. Cormack, and A. C. Bovik. Full-reference quality assessment of stereopairs accounting for rivalry. Signal Processing: Image Communication, 28(9):1143–1155, 2013. [17] V. De Silva, H. Arachchi, E. Ekmekcioglu, and A. Kondoz. Toward an impairment metric for stereoscopic video: A full-reference video quality metric to assess compressed stereoscopic video. IEEE Transactions on Image Processing, 22(9):3392–3404, 2013. [18] J. Ding and G. Sperling. A gain-control theory of binocular combination. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 103(4):1141–1146, 2006. [19] P. Gorley and N. Holliman. Stereoscopic image quality metrics and compression. Proc. SPIE Electronic Imaging, Stereoscopic Displays and Applications XIX, 6803:1–12, 2008. [20] S. Grossberg and F. Kelly. Neural dynamics of binocular brightness perception. Vision Research, 39(22):3796–3816, 1999. [21] C. Hewage and M. Martini. Reduced-reference quality metric for 3d depth map transmission. 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON) 2010, pages 1–4, 2010. [22] C. Hewage, S. Worrall, S. Dogan, and A. Kondoz. Prediction of stereoscopic video quality using objective quality models of 2-d video. Electronics Letters, 44(16):963–965, 31 2008. [23] C. Hewage, S. Worrall, S. Dogan, S. Villette, and A. Kondoz. Quality evaluation of color plus depth map-based stereoscopic video. IEEE Journal of Selected Topics in Signal Processing, 3(2):304–318, Apr. 2009. [24] I. P. Howard and B. J. Rogers. Seeing in Depth. Oxford University Press, USA, 2008. [25] L. Jin, A. Boev, A. Gotchev, and K. Egiazarian. 3d-dct based perceptual quality assessment of stereo video. IEEE ICIP 2011, pages 2521–2524, Sep. 2011. [26] H. Kumano, S. Tanabe, and I. Fujita. Spatial frequency integration for binocular correspondence in macaque area v4. Journal of Neurophysiology, 99(1):402–408, 2008. [27] M. Lambooij, W. IJsselsteijn, D. Bouwhuis, and I. Heynderickx. Evaluation of stereoscopic images: Beyond 2d quality. IEEE Trans. on Broadcasting, 57(2):432–444, Jun. 2011. [28] P. Lebreton, A. Raake, M. Barkowsky, and P. Le Callet. Evaluating depth perception of 3d stereoscopic videos. IEEE Journal of Selected Topics in Signal Processing, 6(6):710 –720, Oct. 2012. [29] G. E. Legge. Spatial frequency masking in human vision: binocular interactions. J. Opt. Soc. Am., 69(6):838–847, 1979. [30] G. E. Legge. Binocular contrast summation-i. detection and discrimination. Vision Research, 24(4):373–383, 1984. [31] G. E. Legge. Binocular contrast summation—ii. quadratic summation. Vision Research, 24(4):385–394, 1984. [32] W. Lin and C.-C. J. Kuo. Perceptual visual quality metrics: A survey. Journal of Visual Communication and Image Representation, 22(4):297–312, 2011. [33] Y.-H. Lin, M.-H. Tsai, and J.-L. Wu. Depth sculpturing for 2d paintings: A progressive depth map completion framework. Journal of Visual Communication and Image Representation, 25(4):670–678, 2014. [34] Y.-H. Lin and J.-L. Wu. A depth information based fast mode decision algorithm for color plus depth-map 3d videos. IEEE Trans. on Broadcasting, 57(2):542–550, Jun. 2011. [35] Y.-H. Lin and J.-L. Wu. A digital blind watermarking for depth-image-based rendering 3d images. IEEE Trans. on Broadcasting, 57(2):602–611, Jun. 2011. [36] Y.-H. Lin and J.-L. Wu. Rendering lossless compression of depth image. IEEE Data Compression Conference 2011, page 467, Mar. 2011. [37] T.-J. Liu, W. Lin, and C.-C. Kuo. Image quality assessment using multi-method fusion. IEEE Trans. on Image Processing, 22(5):1793–1807, 2013. [38] Y. Liu, L. Cormack, and A. Bovik. Statistical modeling of 3-d natural scenes with application to bayesian stereopsis. IEEE Trans. on Image Processing, 20(9):2515–2530, Sep. 2011. [39] A. Maalouf and M.-C. Larabi. Cyclop: A stereo color image quality assessment metric. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2011, pages 1161–1164, 2011. [40] Z. Mai, C. Doutre, P. Nasiopoulos, and R. K. Ward. Rendering 3-d high dynamic range images: Subjective evaluation of tone-mapping methods and preferred 3-d image attributes. IEEE Journal of Selected Topics in Signal Processing, 6(5):597–610, Sep. 2012. [41] J. Mannos and D. Sakrison. The effects of a visual fidelity criterion of the encoding of images. IEEE Transactions on Information Theory, 20(4):525–536, 1974. [42] D. Marr. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. MIT Press, 2010. [43] D. Marr and E. Hildreth. Theory of edge detection. Proc. R. Soc. Lond. B, 207(1167):187–217, Feb. 1980. [44] D. Marr and T. Poggio. A computational theory of human stereo vision. Proc. R. Soc. B-Biol. Sci., 204:301–328, 1979. [45] G. Mather. Foundations of sensation and perception. Psychology Press, 2008. [46] T. S. Meese, M. A. Georgeson, and D. H. Baker. Binocular contrast vision at and above threshold. Journal of Vision, 6(11), 2006. [47] L. Meesters, W. IJsselsteijn, and P. Seuntiens. A survey of perceptual evaluations and requirements of three-dimensional tv. IEEE Trans. on Circuits and Systems for Video Technology, 14(3):381–391, Mar. 2004. [48] M. Mikkola, S. Jumisko-Pyykko, D. Strohmeier, A. Boev, and A. Gotchev. Stereoscopic depth cues outperform monocular ones on autostereoscopic display. IEEE Journal of Selected Topics in Signal Processing, 6(6):698 –709, Oct. 2012. [49] A. K. Moorthy, C.-C. Su, A. Mittal, and A. C. Bovik. Subjective evaluation of stereoscopic image quality. Signal Processing: Image Communication, 28(8):870–883, 2013. [50] I. Ohzawa, G. DeAngelis, and R. Freeman. Stereoscopic depth discrimination in the visual cortex: neurons ideally suited as disparity detectors. Science, 249(4972):1037–1041, 1990. [51] M. Park, J. Luo, and A. C. Gallagher. Toward assessing and improving the quality of stereo images. IEEE Journal of Selected Topics in Signal Processing, 6(5):460–470, Sep. 2012. [52] M. Sampat, Z. Wang, S. Gupta, A. Bovik, and M. Markey. Complex wavelet structural similarity: A new image similarity index. IEEE Trans. on Image Processing, 18(11):2385–2401, Nov. 2009. [53] G. Saygili, C. Gurler, and A. Tekalp. Evaluation of asymmetric stereo video coding and rate scaling for adaptive 3d video streaming. IEEE Trans. on Broadcasting, 57(2):593–601, Jun. 2011. [54] S. Scher, J. Liu, R. Vaish, P. Gunawardane, and J. Davis. 3d+2dtv: 3d displays with no ghosting for viewers without glasses. ACM Transactions on Graphics (TOG), 32(3):21, 2013. [55] P. Seuntiens, L. Meesters, and W. Ijsselsteijn. Perceived quality of compressed stereoscopic images: Effects of symmetric and asymmetric jpeg coding and camera separation. ACM Trans. on Applied Perception, 3(2):95–109, Apr. 2006. [56] F. Shao, W. Lin, S. Gu, G. Jiang, and T. Srikanthan. Perceptual full-reference quality assessment of stereoscopic images by considering binocular visual characteristics. IEEE Transactions on Image Processing, 22(5):1940–1953, 2013. [57] H. Sheikh and A. Bovik. Image information and visual quality. IEEE Trans. on Image Processing, 15(2):430–444, Feb. 2006. [58] H. Sheikh, M. Sabir, and A. Bovik. A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Trans. on Image Processing, 15(11):3440–3451, Nov. 2006. [59] L. Shen, J. Yang, and Z. Zhang. Stereo picture quality estimation based on a multiple channel hvs model. International Congress on Image and Signal Processing, pages 1–4, 2009. [60] M. Solh and G. AlRegib. Miqm: A multicamera image quality measure. IEEE Transactions on Image Processing, 21(9):3902–3914, Sep. 2012. [61] S. Steinman, B. Steinman, and R. Garzia. Foundations of Binocular Vision: A Clinical Perspective. McGraw-Hill Medical, 1 edition, 2000. [62] D. Stidwill and R. Fletcher. Normal Binocular Vision: Theory, Investigation and Practical Aspects. Wiley-Blackwell, 1 edition, 2010. [63] Y. Tong, H. Konik, F. Cheikh, and A. Tremeau. Full reference image quality assessment based on saliency map analysis. Journal of Imaging Science, 54(3):30503–1–30503–14, 2010. [64] Z. Wang and A. Bovik. A universal image quality index. IEEE Signal Processing Letters, 9(3):81–84, Mar. 2002. [65] Z. Wang and A. Bovik. Mean squared error: Love it or leave it? a new look at signal fidelity measures. IEEE Signal Processing Magazine, 26(1):98–117, Jan. 2009. [66] Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli. Image quality assessment: from error visibility to structural similarity. IEEE Trans. on Image Processing, 13(4):600–612, Apr. 2004. [67] Z. Wang, E. Simoncelli, and A. Bovik. Multiscale structural similarity for image quality assessment. In Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, 2004., volume 2, pages 1398–1402, Nov. 2003. [68] H. R. Wilson. Quantitative characterization of two types of line-spread function near the fovea. Vision Research, 18(8):971–981, 1978. [69] H. R. Wilson and J. R. Bergen. A four mechanism model for threshold spatial vision. Vision Research, 19:19–32, 1979. [70] J. Yang, C. Hou, Y. Zhou, Z. Zhang, and J. Guo. Objective quality assessment method of stereo images. 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video, 2009, pages 1–4, 2009. [71] J. You, L. Xing, A. Perkis, and X. Wang. Perceptual quality assessment for stereoscopic images based on 2d image quality metrics and disparity analysis. International Workshop on Video Processing and Quality Metrics (VPQM) 2010, pages 1–6, 2010. [72] G. Zhai, J. Cai, W. Lin, X. Yang, and W. Zhang. Three dimensional scalable video adaptation via user-end perceptual quality assessment. IEEE Trans. on Broadcasting, 54(3):719–727, Sep. 2008. [73] Y. Zhao, Z. Chen, C. Zhu, Y.-P. Tan, and L. Yu. Binocular just-noticeable-difference model for stereoscopic images. IEEE Signal Processing Letters, 18(1):19–22, 2011. [74] Z. Zhu and Y. Wang. Perceptual distortion metric for stereo video quality evaluation. WSEAS Transactions on Signal Processing, 5(7):241–250, Jul. 2009. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56839 | - |
| dc.description.abstract | 三維影像的客觀品質評估方法在三維多媒體相關的應用以及壓縮等相關標準中扮演著關鍵的角色。有關三維影像的品質評估的研究問題，相對於二維影像而言，面臨著許多嶄新的挑戰，例如非對稱式三維影像壓縮、深度知覺的感受以及虛擬視角的影像合成等。更甚者，目前廣泛被使用的二維品質評估的計算方法(例如PSNR與SSIM)並無法有效地處理這些新興的挑戰。其三維影像所計算出的品質評估結果與使用者對於三維影像的主觀評測分數並未能獲得高度一致的結果證明了此一論點。本論文為了因應這些新興的挑戰，除了原有的二維影像評估方式外，有關雙眼整合的視覺行為-雙眼結合以及雙眼頻率整合也首次被應用在三維影像的品質評估上。此一新提出的品質評估方式將藉由已公開的主觀評測分數資料庫進行驗證。實驗結果顯示本研究所提出的三維影像品質評估方式與主觀評測的分數具有顯著一致的結果，其相關係數可高達0.88。再者，我們發現所提出的新品質評估方式也可以有效地評估有關合成的三維影像的品質。因此，我們相信此類的雙眼視覺整合行為在發展三維影像客觀品質評估的過程中應扮演著重要的角色。 | zh_TW |
| dc.description.abstract | The objective approaches to 3D image quality assessment play a key role in the development of compression standards and various 3D multimedia applications. The quality assessment of 3D images faces more new challenges, such as asymmetric stereo compression, depth perception, and virtual view synthesis, than its 2D counterparts. Moreover, the widely used 2D image quality metrics (e.g. PSNR and SSIM) cannot be directly applied to deal with these newly introduced challenges. This statement can be verified by the low correlation between the computed objective measures and the subjectively measured mean opinion scores (MOS's), when 3D images are the tested targets. In order to meet these newly introduced challenges, in this work, besides traditional 2D image metrics, the binocular integration behaviors - the Binocular Combination and the Binocular Frequency Integration (BFI), are utilized as the bases for measuring the quality of stereoscopic 3D images. The effectiveness of the proposed metrics is verified by conducting subjective evaluations on publicly available stereoscopic image databases. Experimental results show that significant consistency could be reached between the measured MOS and the proposed metrics, in which the correlation coefficient between them can go up to 0.88. Furthermore, we found that the proposed metrics can also address the quality assessment of the synthesized color-plus-depth 3D images well. Therefore, it is our belief that the binocular integration behaviors are important factors in the development of objective quality assessment for 3D images. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T05:51:47Z (GMT). No. of bitstreams: 1 ntu-103-D98944008-1.pdf: 4621728 bytes, checksum: 8e7ce180f79fe7c9bbe84ea3c821ad51 (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | 摘要ii
Abstract iii 1 Introduction 1 2 Previous Research Works in 2D/3D IQA Models 5 2.1 Subjective Evaluation Methods . . . . . . . . . . . . . . . . . . . . . . . 6 2.2 2D IQA Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2.1 The Gap between 2D IQA Models and 3D IQA Models . . . . . . 11 2.3 3D IQA Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.3.1 Color Information only . . . . . . . . . . . . . . . . . . . . . . . 11 2.3.2 Color plus Disparity Information . . . . . . . . . . . . . . . . . . 13 2.3.3 Comparison among 3D IQA Models . . . . . . . . . . . . . . . . 14 3 Related Studies of Binocular Visual System 16 3.1 The Visual Response of HVS . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2 The Two Visual Pathways of Binocular Visual System . . . . . . . . . . 17 3.3 Neural Mechanisms of Binocular Combination Behaviors . . . . . . . . . 18 3.3.1 The Binocular Brightness Combination . . . . . . . . . . . . . . 18 3.4 Visual Information Processing from V1 to V4 . . . . . . . . . . . . . . . 21 4 The Proposed Computational Framework 23 4.1 Difference-of-Gaussian Decomposition of Stereo Images . . . . . . . . . 24 4.2 The Binocular Combination and Frequency Integration . . . . . . . . . . 26 4.3 Frequency Integrated Quality Metrics (FI-Metrics) . . . . . . . . . . . . 27 5 Experimental Results 29 5.1 Subjective Data Collection of CML Database . . . . . . . . . . . . . . . 29 5.2 The Number of Frequency bands for FI-metrics . . . . . . . . . . . . . . 33 5.3 The Performance Evaluation of FI-Metrics . . . . . . . . . . . . . . . . . 34 5.4 The Quality Assessment of Symmetric-Stereo Compression . . . . . . . . 36 5.5 The Quality Assessment of Asymmetric-Stereo Compression . . . . . . . 37 5.6 The Quality Assessment of All Compression Combinations . . . . . . . . 38 5.7 The Correlation between the Picture Quality Measure and the Depth Quality Measure . . . . 38 5.8 The Indirect Quality Assessment of Synthesized Stereo Images . . . . . . 40 5.9 The 3D IQA Model Comparisons on CML database . . . . . . . . . . . . 42 5.10 Proposed Metrics on 3D Video Compression Database . . . . . . . . . . 43 5.11 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 5.12 Binocular Perceptual RD Performance of Asymmetric-Stereo Compression 48 5.13 Proposed Metrics for Different Distortion Types . . . . . . . . . . . . . . 49 6 Discussions and Conclusion 52 Bibliography 53 | |
| dc.language.iso | en | |
| dc.subject | 影像品質 | zh_TW |
| dc.subject | 雙眼視覺 | zh_TW |
| dc.subject | 三維影像 | zh_TW |
| dc.subject | 壓縮 | zh_TW |
| dc.subject | 訊號處理 | zh_TW |
| dc.subject | Binocular Vision | en |
| dc.subject | Image Quality | en |
| dc.subject | 3D Image | en |
| dc.subject | Compression | en |
| dc.subject | Signal Processing | en |
| dc.title | 雙眼視覺品質評估之研究及其應用 | zh_TW |
| dc.title | A Study of Binocular Quality Assessment and Its Applications | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 李琳山,貝蘇章,陳宏銘,廖弘源,杭學鳴 | |
| dc.subject.keyword | 影像品質,雙眼視覺,三維影像,壓縮,訊號處理, | zh_TW |
| dc.subject.keyword | Image Quality,Binocular Vision,3D Image,Compression,Signal Processing, | en |
| dc.relation.page | 60 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-08-08 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
| 顯示於系所單位： | 資訊網路與多媒體研究所 | |
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