基于區(qū)間估計的單幅圖像快速去霧
doi: 10.11999/JEIT150403
-
2.
(武漢理工大學(xué)光纖傳感與信號處理教育部重點實驗室 武漢 430070) ②(湖南工學(xué)院電氣與信息工程學(xué)院 衡陽 421002) ③(武漢理工大學(xué)交通學(xué)院 武漢 430070)
國家自然科學(xué)基金(51479159),交通運輸部軟科學(xué)項目(2013-322-811-470)
Fast Single Image Dehazing Based on Interval Estimation
-
2.
(Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China)
The National Natural Science Foundation of China (51479159), Soft Science Project of Chinas Ministry of Transport (2013-322-811-470)
-
摘要: 針對霧、霾等天氣條件下捕獲的圖像存在嚴重降質(zhì)現(xiàn)象,該文提出一種基于區(qū)間估計的單幅圖像快速去霧方法。該方法從大氣散射模型出發(fā),基于暗通道先驗理論,利用最小值濾波和灰度開運算,通過區(qū)間估計得到大氣光值,同時得到介質(zhì)傳輸率的初始估計值。通過對大氣光照進行白平衡處理,從而得到簡化大氣散射模型。然后,利用簡化大氣散射模型和介質(zhì)傳輸率的初始估計值,通過區(qū)間估計得到場景反照率的暗通道值,進一步得到介質(zhì)傳輸率的粗略估計值。將介質(zhì)傳輸率的初始估計值和粗略估計值進行像素級融合,通過聯(lián)合雙邊濾波和值域調(diào)整得到介質(zhì)傳輸率的最終估計值。最后,通過簡化大氣散射模型和色調(diào)調(diào)整得到去霧圖像。實驗結(jié)果表明,所提算法具有較快的運算速度,能有效提高去霧圖像的清晰度和對比度,同時獲得較好的色調(diào)保真度。Abstract: In order to solve the problem of degraded images captured in hazy weather, a single image dehazing method based on interval estimation is proposed. From the atmospheric scattering model, the minimal filtering and gray-scale opening operation are used to estimate the value of atmospheric light based on dark channel prior theory. At the same time, the initial estimated value of medium transmission is defined. Then, the white balance is performed and the atmospheric scattering model is simplified. Secondly, the simplified atmospheric scattering model and initial estimated value of medium transmission are used to estimate the dark channel value of scene albedo, which is adopted to obtain the coarse estimated value of medium transmission. The final estimated value of medium transmission is obtained by getting through image fusion, joint bilateral filtering and range adjustment. Finally, the simplified atmospheric scattering model and tone mapping are adopted to get the restored image. Experimental results show that the proposed algorithm has a high computation speed, effectively improves the clarity and contrast of restored image, and obtains good color fidelity.
-
Key words:
- Image dehazing /
- Interval estimation /
- Dark channel prior /
- Image fusion /
- Bilateral filtering
-
TAN R T. Visibility in bad weather from a single image [C]. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, AK, 2008: 1-8. FATTAL R. Single image dehazing[J]. ACM Transactions on Graphics, 2008, 27(3): 1-9. HE Kaiming, SUN Jian, and TANG Xiaoou. Single image haze removal using dark channel prior[C]. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Miami, FL, 2009: 1956-1963. TAREL J P and HAUTIERE N. Fast visibility restoration from a single color or gray level image[C]. Proceedings of IEEE International Conference on Computer Vision, Kyoto, 2009: 2201-2208. 方帥, 王勇, 曹洋, 等. 單幅霧天圖像復(fù)原[J]. 電子學(xué)報, 2010, 38(10): 2279-2284. FANG Shuai, WANG Yong, CAO Yang, et al. Restoration of image degraded by haze[J]. Acta Electronica Sinica, 2010, 38(10): 2279-2284. 禹晶, 李大鵬, 廖慶敏. 基于物理模型的快速單幅圖像去霧方法[J]. 自動化學(xué)報, 2011, 37(2): 143-149. YU Jing, LI Dapeng, and LIAO Qingmin. Physics-based fast single image fog removal[J]. Acta Automatica Sinica, 2011, 37(2): 143-149. ANCUTI C O and ANCUTI C. Single image dehazing by multi-scale fusion[J]. IEEE Transactions on Image Processing, 2013, 22(8): 3271-3282. SUN Wei. A new single image fog removal algorithm based on physical model[J]. International Journal for Light and Electron Optics, 2013, 124(21): 4770-4775. CARDEI V, FUNT B, and BARNARD K. White point estimation for uncalibrated images[C]. Proceedings of the 7th IS and T/SID Color Imaging Conference: Color Science, Systems and Applications, Scottsdale, 1999: 97-100. 黃立勤, 陳財淦. 全景圖拼接中圖像融合算法的研究[J]. 電子與信息學(xué)報, 2014, 36(6): 1292-1298. doi: 10.3724/SP.J.1146. 2013.01220. HUANG Liqin and CHEN Caigan. Study on image fusion algorithm of panoramic image stitching[J]. Journal of Electronics Information Technology, 2014, 36(6): 1292-1298. doi: 10.3724/SP.J.1146.2013.01220. 張小剛, 唐美玲, 陳華, 等.一種結(jié)合雙區(qū)域濾波和圖像融合的單幅圖像去霧算法[J]. 自動化學(xué)報, 2014, 40(8): 1733-1739. ZHANG Xiaogang, TANG Meiling, CHEN Hua, et al. A dehazing method in single image based on double-area filter and image fusion[J]. Acta Automatica Sinica, 2014, 40(8): 1733-1739. PARIS M and FREDE D. A fast approximation of the bilateral filter using a signal processing approach[C]. Proceedings of the 9th European Conference on Computer Vision, Graz, 2006: 568-580. 孫小明, 孫俊喜, 趙立榮, 等. 暗原色先驗單幅圖像去霧改進算法[J]. 中國圖像圖形學(xué)報, 2014, 19(3): 0215-0220. SUN Xiaoming, SUN Junxi, ZHAO Lirong, et al. Improved algorithm for single image haze removing using dark channel prior[J]. Journal of Image and Graphics, 2014, 19(3): 0215-0220. 吳笑天, 魯劍鋒, 賀柏根, 等. 霧天降質(zhì)圖像的快速復(fù)原[J].中國光學(xué), 2013, 6(6): 892-899. WU Xiaotian, LU Jianfeng, HE Bogen, et al. Fast restoration of haze-degraded image[J]. Chinese Optics, 2013, 6(6): 892-899. 甘佳佳, 肖春霞. 結(jié)合精確大氣散射圖計算的圖像快速去霧[J]. 中國圖像圖形學(xué)報, 2013, 18(5): 583-590. GAN Jiajia and XIAO Chunxia. Fast image dehazing based on accurate scattering map[J]. Journal of Image and Graphics, 2013, 18(5): 583-590. DRAGO F, MYSZKOWSKI K, ANNEN T, et al. Adaptive logarithmic mapping for displaying high contrast scenes[J]. Computer Graphics Forum, 2003, 22(3): 419-426. 南棟, 畢篤彥, 查宇飛, 等. 基于參數(shù)估計的無參考型圖像質(zhì)量評價算法[J]. 電子與信息學(xué)報, 2013, 35(9): 2066-2072. doi: 10.3724/SP.J.1146. 2012.01652. NAN Dong, BI Duyan, Zha Yufei, et al. A no-reference image quality assessment method based on parameter estimation[J]. Journal of Electronics Information Technology, 2013, 35(9): 2066-2072. doi: 10.3724/SP.J.1146.2012.01652. 豐明坤, 趙生妹, 邢超. 基于視覺顯著失真度的圖像質(zhì)量自適應(yīng)評價方法[J]. 電子與信息學(xué)報, 2015, 37(9): 2062-2068. doi: 10.11999/JEIT141641. FENG Mingkun, ZHAO Shengmei, and XING Chao. Image quality self-adaptive assessment based on visual salience distortion[J]. Journal of Electronics Information Technology, 2015, 37(9): 2062-2068. doi: 10.11999/ JEIT141641. HAUTIERE N, TAREL J P, AUBERT D, et al. Blind contrast restoration assessment by gradient ratioing at visible edges[J]. Image Analysis and Stereology, 2008, 27(2): 87-95. 郭璠, 蔡自興, 謝斌. 基于霧氣理論的視頻去霧算法[J]. 電子學(xué)報, 2011, 39(9): 2019-2025. GUO Fan, CAI Zixing, and XIE Bin. Video defogging algorithm based on fog theory[J]. Acta Electronica Sinica, 2011, 39(9): 2019-2025. JOBSON D J, RAHMAN Z, and WOODELL G A. The statistics of visual representation[C]. Proceedings of the Visual Information Processing XI, Orlando, 2002, 4736: 25-35. 李菊霞, 余雪麗. 霧天條件下的多尺度Retinex圖像增強算法[J]. 計算機科學(xué), 2013, 40(3): 299-301. LI Juxia and YU Xueli. Enhance algorithm for fog images based on improved multi-scale Retinex[J]. Computer Science, 2013, 40(3): 299-301. KOPF J, NEUBERT B, CHEN B, et al. Deep photo: model-based photograph enhancement and viewing[J]. ACM Transactions on Graphics, 2008, 27(5): 116:1-116:10. NISHINO K, KRATZ L, and LOMBARDI S. Bayesian defogging[J]. International Journal of Computer Vision, 2012, 98(3): 263-278. -
計量
- 文章訪問數(shù): 1856
- HTML全文瀏覽量: 238
- PDF下載量: 2619
- 被引次數(shù): 0