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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/78810完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 盧奕璋 | zh_TW |
| dc.contributor.advisor | Yi-Chang Lu | en |
| dc.contributor.author | 吳岳霖 | zh_TW |
| dc.contributor.author | Yueh-Lin Wu | en |
| dc.date.accessioned | 2021-07-11T15:21:01Z | - |
| dc.date.available | 2024-02-14 | - |
| dc.date.copyright | 2019-02-18 | - |
| dc.date.issued | 2019 | - |
| dc.date.submitted | 2002-01-01 | - |
| dc.identifier.citation | Bibliography
[1] Artstation kuan-ju chen. https://www.artstation.com/sinnra. Accessed: 2018-12-27. [2] Color attenuation prior dehazing. https://github.com/JiamingMai/Color-Attenuation-Prior-Dehazing. Accessed: 2018-12-27. [3] Single image haze removal using dark channel prior demo. https://blog.csdn.net/hit1524468/article/details/79770058. Accessed: 2018-12-27. [4] C. O. Ancuti and C. Ancuti. Single image dehazing by multi-scale fusion. IEEE Transactions on Image Processing, 22(8):3271–3282, 2013. [5] D. Berman, S. Avidan, et al. Non-local image dehazing. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 1674–1682, 2016. [6] D. Berman, T. Treibitz, and S. Avidan. Air-light estimation using haze-lines. In Computational Photography (ICCP), 2017 IEEE International Conference on, pages 1–9. IEEE, 2017. [7] K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian. Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Transactions on image processing, 16(8):2080–2095, 2007. [8] V. H. Diaz-Ramirez, J. E. Hernández-Beltrán, and R. Juarez-Salazar. Real-time haze removal in monocular images using locally adaptive processing. Journal of Real-Time Image Processing, pages 1–15. [9] R. Fattal. Single image dehazing. ACM transactions on graphics (TOG), 27(3):72, 2008. [10] C. Feng, S. Zhuo, X. Zhang, L. Shen, and S. Süsstrunk. Near-infrared guided color image dehazing. In Proc. IEEE 20th International Conference on Image Processing (ICIP), number EPFL-CONF-188639, pages 2363–2367, 2013. [11] N. Hautière, J.-P. Tarel, D. Aubert, and E. Dumont. Blind contrast enhancement assessment by gradient ratioing at visible edges. Image Analysis & Stereology, 27(2):87–95, 2011. [12] K. He, J. Sun, and X. Tang. Single image haze removal using dark channel prior. IEEE transactions on pattern analysis and machine intelligence, 33(12):2341–2353, 2011. [13] K. He, J. Sun, and X. Tang. Guided image filtering. IEEE transactions on pattern analysis & machine intelligence, (6):1397–1409, 2013. [14] H. Koschmieder. Theorie der horizontalen sichtweite. Beitrage zur Physik der freien Atmosphare, pages 33–53, 1924. [15] A. Levin, D. Lischinski, and Y. Weiss. A closed-form solution to natural image matting. IEEE transactions on pattern analysis and machine intelligence, 30(2):228–242, 2008. [16] S. G. Narasimhan and S. K. Nayar. Vision and the atmosphere. International Journal of Computer Vision, 48(3):233–254, 2002. [17] L. Schaul, C. Fredembach, and S. Süsstrunk. Color image dehazing using the nearinfrared. In Proc. IEEE International Conference on Image Processing (ICIP), number LCAV-CONF-2009-026, 2009. [18] R. T. Tan. Visibility in bad weather from a single image. In Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pages 1–8. IEEE, 2008. [19] J.-P. Tarel and N. Hautiere. Fast visibility restoration from a single color or gray level image. In Computer Vision, 2009 IEEE 12th International Conference on, pages 2201–2208. IEEE, 2009. [20] C. Tomasi and R. Manduchi. Bilateral filtering for gray and color images. In Computer Vision, 1998. Sixth International Conference on, pages 839–846. IEEE, 1998. [21] Y. Xu, J. Wen, L. Fei, and Z. Zhang. Review of video and image defogging algorithms and related studies on image restoration and enhancement. Ieee Access, 4:165–188, 2016. [22] Q. Zhu, J. Mai, L. Shao, et al. A fast single image haze removal algorithm using color attenuation prior. IEEE Trans. Image Processing, 24(11):3522–3533, 2015. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/78810 | - |
| dc.description.abstract | 霧是一種常見會影響能見度及對比度的大氣現象，其原因來自於大氣粒子散射環境光造成，其影響程度和物體與相機接收端之距離呈正相關。單張影像去霧因為其輸入資訊較少，在影像處理中屬於極富挑戰性的非良置性問題，也因此近年來有大量研究投入。本論文提出新式的單張影像去霧演算法屬於穿透率去霧演算法，使用顏色在RGB空間中之夾角找出環境光，再藉由環境光夾角調整關鍵通道縮放的概念反推穿透率，並進一步使用引導影像濾波器將穿透率加入空間平滑性。除了影像去霧外，本論文也針對穿透率去霧結果進行後處理，包含了亮度修正、顏色突出兩個部分，對於去霧後的亮度和色彩分別進行補償以得到品質更好的影像。
相關研究往往會有去霧影像過暗及運算時間過長等問題，本論文提出之全新單張影像去霧演算法去霧效果佳，不會使去霧影像過暗；且運算時間相當快速，適合應用在即時影片去霧，提升行車安全。提出之後處理演算法通用性相當高，可以銜接在相關穿透率去霧研究以調整去霧結果。 | zh_TW |
| dc.description.abstract | Haze is a common atmospheric phenomenon that can significantly degrade the visibility and contrast of a scene. The main cause of it is air-light scattering by the particles in the atmosphere. The impact of haze and the depth of the object are positively correlated. Single image dehazing is a challenging ill-posed problem in image processing because of the insufficiency of input information. Therefore, there were many researches focused on this issue these years. In this thesis, we propose a fast and novel transmission-based single image dehazing algorithm, using the angles of colors in RGB space to estimate air-light. Then we scale the critical channel value of the image by considering the angles between the image color and air-light color. Then we can use the value of the critical channel to estimate the transmission and refine it by applying a guided image filter. We also propose luminance correction and stand-out color enhancement algorithm for post-processing of image dehazing, in order to deal with over-dehazing and low contrast problem in dehazed image, respectively.
The related works are often suffered from either over-dehazing issue or lengthy computation time. The proposed dehazing algorithm has well dehazing result without over-dehazed effect. Besides, the computation time is short so that it is ideal for video dehazing. The proposed post-processing algorithms can adjust the dehazed results and they are both suited for transmission-based image dehazing algorithms. | en |
| dc.description.provenance | Made available in DSpace on 2021-07-11T15:21:01Z (GMT). No. of bitstreams: 1 ntu-108-R05943119-1.pdf: 74340551 bytes, checksum: 796b6c3b3fab94e476c62e7b94c1f0c0 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 1 緒論1
1.1 去霧動機 2 1.2 相關研究 2 1.2.1 穿透率去霧演算法 3 1.2.2 融合影像去霧法 7 1.2.3 加強對比度去霧法 8 1.3 論文架構 8 2 背景知識11 2.1 成霧模型 11 2.2 引導影像濾波器 13 2.3 三維塊匹配演算法 15 3 演算法19 3.1 演算法概述 19 3.2 環境光估測與夾角 19 3.2.1 環境光夾角計算 20 3.2.2 環境光夾角正規化 20 3.2.3 環境光估測 22 3.3 關鍵通道 28 3.3.1 穿透率下界 28 3.3.2 關鍵通道縮放 30 3.4 穿透率估測與精化 33 3.4.1 穿透率估測 33 3.4.2 穿透率精化 35 3.5 影像去霧 38 3.6 後處理 39 3.6.1 亮度修正 40 3.6.2 突出演算法 44 3.6.3 消除雜訊 47 4 參數與去霧結果49 4.1 參數介紹與實驗 49 4.2 與其他論文去霧結果之比較 51 4.2.1 定性分析 53 4.2.2 定量分析 56 4.3 運算時間比較 58 5 結論61 5.1 結論 61 5.2 展望 61 Bibliography 63 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 快速單張影像去霧 | zh_TW |
| dc.subject | 環境光夾角 | zh_TW |
| dc.subject | 關鍵通道縮放 | zh_TW |
| dc.subject | 亮度修正後處理 | zh_TW |
| dc.subject | 顏色突出後處理 | zh_TW |
| dc.subject | critical channel scaling | en |
| dc.subject | luminance correction | en |
| dc.subject | stand-out color enhancement | en |
| dc.subject | single image dehazing | en |
| dc.subject | air-light angle | en |
| dc.title | 使用關鍵通道縮放與環境光夾角調整之快速單張影像去霧技術 | zh_TW |
| dc.title | Fast Single Image Dehazing Using Critical Channel Scaling with Air-Light Angle Adjustment | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 107-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 丁建均;王鈺強 | zh_TW |
| dc.contributor.oralexamcommittee | Jian-Jiun Ding;Yu-Chiang Wang | en |
| dc.subject.keyword | 快速單張影像去霧,環境光夾角,關鍵通道縮放,亮度修正後處理,顏色突出後處理, | zh_TW |
| dc.subject.keyword | single image dehazing,air-light angle,critical channel scaling,luminance correction,stand-out color enhancement, | en |
| dc.relation.page | 65 | - |
| dc.identifier.doi | 10.6342/NTU201900528 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2019-02-15 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 電子工程學研究所 | - |
| dc.date.embargo-lift | 2024-02-18 | - |
| 顯示於系所單位： | 電子工程學研究所 | |
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|---|---|---|---|
| ntu-107-1.pdf 未授權公開取用 | 72.6 MB | Adobe PDF |
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