Rain Removal From Still Images Using L0 Gradient Minimization Technique

被引:0
|
作者
Manu, B. N.
机构
来源
2015 7TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND ELECTRICAL ENGINEERING (ICITEE) | 2015年
关键词
rain removal; L-0 gradient minimization; smoothing; connected components;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Removal of rain from still images is a complex and a challenging task. The rain drops affects only on a very small region of an image, and hence, leading to a confusion to determine which region should be considered and which should not. In this paper, a new technique has been implemented which effectively uses the L-0 gradient minimization approach to remove the rain pixels. The minimization technique can globally control how many non-zero gradients are resulted in the image. The method is independent of local features, but instead locates important edges globally. These salient edges are preserved and low amplitude and insignificant details are diminished. The rain pixels are removed in this manner. Finally the rain removed images are enhanced in intensity using histogram adjustment technique to get better contrast images. Experimental results show that the proposed algorithm is highly efficient as it removes rain effectively even under heavy rain conditions, while preserving the details of the image.
引用
收藏
页码:263 / 268
页数:6
相关论文
共 50 条
  • [1] Video segmentation with L0 gradient minimization
    Cheng, Xuan
    Feng, Yuanli
    Zeng, Ming
    Liu, Xinguo
    COMPUTERS & GRAPHICS-UK, 2016, 54 : 38 - 46
  • [2] An efficient method for scanned images by using color-correction and L0 gradient minimization
    Ji, Jing
    Fang, Suping
    Xia, Qing
    Shi, Zhengyuan
    OPTIK, 2021, 247
  • [3] Image Smoothing via L0 Gradient Minimization
    Xu, Li
    Lu, Cewu
    Xu, Yi
    Jia, Jiaya
    ACM TRANSACTIONS ON GRAPHICS, 2011, 30 (06):
  • [4] Surface reconstruction from unorganized points with l0 gradient minimization
    Li, Huibin
    Li, Yibao
    Yu, Ruixuan
    Sun, Jian
    Kim, Junseok
    COMPUTER VISION AND IMAGE UNDERSTANDING, 2018, 169 : 108 - 118
  • [5] Edge-Aware Volume Smoothing Using L0 Gradient Minimization
    Wang, Qichao
    Tao, Yubo
    Lin, Hai
    COMPUTER GRAPHICS FORUM, 2015, 34 (03) : 131 - 140
  • [6] Depth Recovery from a single image based on L0 Gradient Minimization
    Cao Fengyun
    Xie Fei
    2018 9TH IEEE INTERNATIONAL CONFERENCE ON BIG KNOWLEDGE (ICBK), 2018, : 336 - 341
  • [7] Spectral Mesh Segmentation via l0 Gradient Minimization
    Tong, Weihua
    Yang, Xiankang
    Pan, Maodong
    Chen, Falai
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2020, 26 (04) : 1807 - 1820
  • [8] Feature-preserving filtering with L0 gradient minimization
    Cheng, Xuan
    Zeng, Ming
    Liu, Xinguo
    COMPUTERS & GRAPHICS-UK, 2014, 38 : 150 - 157
  • [9] Natural Image Dehazing Based on L0 Gradient Minimization
    Qi, Jingjing
    Lu, Wen
    Yang, Shuyu
    Gao, Xinbo
    INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING: IMAGE AND VIDEO DATA ENGINEERING, ISCIDE 2015, PT I, 2015, 9242 : 603 - 610
  • [10] Fast and Effective L0 Gradient Minimization by Region Fusion
    Nguyen, Rang M. H.
    Brown, Michael S.
    2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2015, : 208 - 216