一种基于反馈机制的闭环图像去雾算法

马时平; 李权合; 张晟翀

doi:10.11999/JEIT150494

一种基于反馈机制的闭环图像去雾算法

doi: 10.11999/JEIT150494

1.
(空军工程大学航空航天工程学院西安 710038) ②(光电信息控制和安全技术重点实验室三河 065201)

基金项目:

国家自然科学基金(61372167, 61379104)

计量
- 文章访问数: 1699
- HTML全文浏览量: 134
- PDF下载量: 315
- 被引次数: 0
出版历程
- 收稿日期: 2015-04-29
- 修回日期: 2015-10-23
- 刊出日期: 2016-02-19

An Adaptive Closed-loop Image Dehazing Algorithm Based on the Feedback Mechanism

1.
(Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an 710038, China)
2.
(Optical Information Control and Security Technology Laboratory, Sanhe 065201, China)

Funds:

The National Natural Science Foundation of China (61372167, 61379104)

摘要

摘要: 针对目前去雾算法易受大气环境随机性和复杂性影响而造成自适应性不强的问题，该文提出一种具有反馈机制的自适应闭环去雾算法。该算法首先通过基于人眼视觉的特征认知评价进行参数初始化；然后利用去雾强度评价结果对反馈校正局部对比度参数进行调节，从而对去除加性光照后的图像进行自适应局部对比度提升；最后借鉴去雾后图像的自然度设定迭代终止条件，决定是否输出去雾结果。实验表明该算法能够自适应提升不同退化类型、不同退化程度下的雾天图像对比度，且去雾结果的信息熵和清晰度质量评价指标优于已有算法。
- 图像去雾 /
- 视觉机制 /
- 反馈机制
Abstract: To solve the problem of low adaptability in existing dehazing algorithms caused by the randomness and complexity of atmospheric environment, an adaptive closed-loop dehazing algorithm based on the feedback mechanism is proposed. Firstly, parameters in the proposed algorithm are initialized according to human visual system based characteristic cognitive assessment. Secondly, the estimation of dehazing strength is given as the feedback to correct parameters of local contrast adjustment method, and then adaptively improve the local contrast of image after removing additive light. Finally, the terminating condition is set according to the naturalness of image after dehazing to determine whether to output the result. Experimental results show that the proposed algorithm can adaptively improve the contrast of hazy images with a variety of degradation types and degrees, and the evaluation of information entropy and definition of dehazing results is better than those of other existing algorithms.
- Image dehaze /
- Visual mechanism /
- Feedback mechanism

HTML全文

参考文献(28)

KRISTOFOR B G and TRUONG Q N. An analysis and method for contrast enhancement turbulence mitigation[J]. IEEE Transactions on Image Processing, 2014, 23(7): 3179-3190.

WANG Y K and FAN C . Single image defogging by multiscale depth fusion[J]. IEEE Transactions on Image Processing, 2014, 23(11): 4826-4837.

SUN X M, SUN J X, ZHAO L R, et al. Improved single image haze removal using dark channel prior[J]. Journal of Image and Graphics, 2014, 19(3): 381-385.

SCHECHNER Y Y, NARASIMHAN S G, and NAYAR S K. Polarization-based vision through haze[J]. Appled Optics, 2003, 42(3): 511-525.

NARASIMHAN S G and NAYAR S K. Contrast restoration of weather degraded images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(6): 713-724.

DING M and TONG R F. Efficient dark channel based image dehazing using quadtrees[J]. SCIENCE CHINA Information Sciences, 2013, 56(9): 231-239.

XIONG Y Q, YAN H, and YU C. Improved haze removal algorithm using dark channel prior[J]. Journal of Computational Information Systems, 2013, 9(14): 5743-5750.

庞春颖, 嵇晓强, 孙丽娜, 等. 一种改进的图像快速去雾新算法[J]. 光子学报, 2013, 42(7): 872-877.

PANG Chunying, JI Xiaoqiang, SUN Lina, et al. An improved method of image fast defogging[J]. Acta Photonica Sinica, 2013, 42(7): 872-877.

GIBSON K B, VO D T, and NGUYEN T Q. An investigation of dehazing effects on image and video coding[J]. IEEE Transactions on Image Processing, 2012, 21(2): 662-673.

KIM J H, JANG W D, SIM J Y, et al. Optimized contrast enhancement for real-time image and video dehazing[J]. Journal of Visual Communication and Image Representation, 2013, 24(3): 410-425.

SHIAU Y H, YANG H Y, CHEN P Y, et al. Hardware implementation of a fast and efficient haze removal method [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2013, 23(8): 1369-1374.

HE K M, SUN J, and TANG X O. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12): 2341-2353.

BOSSU J, HAUTIERE N, and TAREL J P. Rain or snow detection in image sequences through use of a histogram of orientation of streaks[J]. International Journal of Computer Vision, 2011, 93(3): 348-367.

NISHINO K, KRATZ L, and LOMBARDI S. Bayesian defogging[J]. International Journal of Computer Vision, 2012, 98(4): 263-278.

方雯, 刘秉瀚. 反馈调节机制的暗通道去雾算法[J]. 计算机应用, 2013, 33(7): 1998-2001.

FANG Wen and LIU Binghan. Dehazing algorithm based on dark channel with feedback regulation mechanism[J]. Journal of Computer Applications, 2013, 33(7): 1998-2001.

WALTHER D and KOCH C. Modeling attention to salient proto-objects[J]. Neural Networks, 2006, 19(9): 1395-1407.

王守觉, 丁兴号, 廖英豪, 等. 一种新的仿生彩色图像增强算法[J]. 电子学报, 2008, 36(10): 1970-1973.

WANG Shoujue, DING Xinghao, LIAO Yinghao, et al. A novel bio-inspired algorithm for color image enhancement[J]. Acta Electronica Sinica, 2008, 36(10): 1970-1973.

PARIS S and DURAND F. A fast approximation of the bilateral filter using a signal processing approach[J]. International Journal of Computer Vision, 2009, 81(1): 24-52.

YANG Q X, TAN K H, and AHUJA N. Real-time O(1) bilateral filtering[C]. Proceedings of the 27th IEEE Conference on Computer Vision and Pattern Recognition, Miami, USA, 2009: 557-564.

KIMMEL R, ELAD M, SHAKED D, et al. A variational framework for Retinex[J]. Computer Vision, 2003, 52(1): 7-23.

HE K M, SUN J, and TANG X O. Single image haze removal using dark channel prior[C]. Proceedings of the 27th IEEE Conference on Computer Vision and Pattern Recognition, Miami, USA, 2009: 1956-1963.

陈季梦, 陈佳俊, 刘杰, 等. 基于结构相似度的大规模社交网络聚类算法[J]. 电子与信息学报, 2015, 37(2): 449-454. doi: 10.11999/JEIT140512.

CHEN Jimeng, CHEN Jiajun, LIU Jie, et al. Clustering algorithm for large-scale social networks based on structural similarity[J]. Journal of Electronics Information Technology, 2015, 37(2): 449-454. doi: 10.11999/JEIT140512.

薛模根, 朱虹, 袁广林. 基于在线判别式字典学习的鲁棒视觉跟踪[J]. 电子与信息学报, 2015, 37(7): 1654-1659. doi: 10.11999/JEIT141325.

XUE Mogen, ZHU Hong, and YUAN Guanglin. Robust visual tracking based on online discrimination dictionary learning[J]. Journal of Electronics Information Technology, 2015, 37(7): 1654-1659. doi: 10.11999/JEIT141325.

施引文献

资源附件(0)

访问统计