[1]葛 朋,杨 波,韩庆林,等.一种基于引导滤波图像分层的红外图像细节增强算法[J].红外技术,2018,40(12):1161-1169.[doi:10.11846/j.issn.1001_8891.201812008]
 GE Peng,YANG Bo,HAN Qinglin,et al.Infrared Image Detail Enhancement Algorithm Based on Hierarchical Processing by Guided Image Filter[J].Infrared Technology,2018,40(12):1161-1169.[doi:10.11846/j.issn.1001_8891.201812008]
点击复制

一种基于引导滤波图像分层的红外图像细节增强算法
分享到:

《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
40
期数:
2018年第12期
页码:
1161-1169
栏目:
出版日期:
2018-12-21

文章信息/Info

Title:
Infrared Image Detail Enhancement Algorithm Based on Hierarchical Processing by Guided Image Filter
文章编号:
1001-8891(2018)12-1161-09
作者:
葛 朋杨 波韩庆林刘 鹏陈树刚胡窦明张巧燕
昆明物理研究所,云南 昆明 650223
Author(s):
GE PengYANG BoHAN QinglinLIU PengCHEN ShugangHU DoumingZHANG Qiaoyan
 Kunming Institute of Physics, Kunming 650223 , China
关键词:
引导滤波图像分层红外图像细节增强
Keywords:
guided image filterhierarchical processinginfrared imagedetail enhancement
分类号:
TP391.41
DOI:
10.11846/j.issn.1001_8891.201812008
文献标志码:
A
摘要:
为了解决高动态红外图像在常规显示设备上显示时容易出现图像整体对比度低、弱小目标细节模糊等问题,提出了一种基于引导滤波图像分层的红外图像细节增强算法,并从算法理论分析和仿真结果两方面验证了引导滤波具有更好的边缘保持能力,能有效避免增强后出现“伪边缘”的缺陷。另外,针对原始全局的引导滤波算法对整幅图像各个区域使用相同的规整化因子,容易产生“光晕”现象的缺陷,本文在局部方差加权引导滤波算法的思想上,提出了基于LoG边缘算子的加权引导滤波算法。实验结果表明本文算法具有良好的细节增强效果,特别是对图像中的弱小目标;另外,相比目前应用广泛的双边滤波算法,本文算法运行时间要快得多,具有实时处理的应用前景。
Abstract:
To solve the problem that high dynamic infrared images are prone to appear with low image contrast and weak target fuzzy details when displayed on a conventional display device, a novel infrared image detail enhancement algorithm based on the hierarchical processing by a guided image filter is proposed. Furthermore, this study has verified that the guided filter has improved ability of edge keeping and can effectively avoid the “pseudo edge” using the theoretical analysis and simulation results. T he original global guide filter algorithm uses the same neat factor among the whole image regions, which makes it is prone to exhibit halos near some edges. Based on the idea of the local variance weighted guided filter, an improved locally weighted guided filter using the Laplacian of Gaussian ( LoG) operator is proposed. The experiments in this study show that this algorithm has good detail enhancement effect, especially for small targets in the images. Additionally, compared to the widely used bilateral filtering algorithm, this algorithm runs considerably faster, and has potential applications in real-time processing.

参考文献/References:

[1] 杨静, 李争. 一种基于双边滤波的红外图像细节增强方法[J]. 激光与红外, 2016, 46(4): 507-511.

YANG Jing, LI Zheng. Detail enhancement method for infrared image based on bilateral filter[J]. Laser and Infrared, 2016, 46(4): 507-511.

[2] HE K, SUN J, TANG X. Guided image filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6): 1397-1409.

[3] 刘婷婷. 红外图像细节增强算法与实现的研究[D]. 成都: 电子科技大学, 2014.

LIU Tingting. Reseach on detail enhancement algorithm and implementation for infrared images[D]. Chengdu: Uinversity of Electronic Science and Technology of China, 2014.

[4] 谢伟, 周玉钦, 游敏. 融合梯度信息的改进引导滤波[J]. 中国图象图形学报, 2016, 21(9): 1119-1126.

XIE Wei, ZHOU Yuqin, YOU Min. Improved guided image filtering integrated with gradient information[J]. Journal of Image and Graphics, 2016, 21(9): 1119-1126.

[5] LI Z, ZHENG J, ZHU Z, et al. Weighted guided image filtering[J]. IEEE Transactions on Image Processing, 2015, 24(1): 120-129.

[6] 龙鹏, 鲁华祥. LoG边缘算子改进的加权引导滤波算法[J]. 计算机应用, 2015, 35(9): 2661-2665.

LONG Peng, LU Huaxiang. Weighted guided image filtering algorithm using Laplacian of Gaussian edge detector[J]. Journal of Computer Applications, 2015, 35 (9): 2661-2665.

[7] 田自君, 刘艺. 基于LoG算子边缘检测的图像二值化处理[J]. 中国测试技术, 2007, 33(6): 109-111.

相似文献/References:

[1]温海滨,毕笃彦,马时平,等.消除光晕和细节增强的多尺度Retinex红外图像增强[J].红外技术,2016,38(2):149.[doi:10.11846/j.issn.1001_8891.201602012]
 WEN Haibin,BI Duyan,MA Shiping,et al.Halo-free and Detail Enhancement Based on Multi-scale Retinex for Infrared Image [J].Infrared Technology,2016,38(12):149.[doi:10.11846/j.issn.1001_8891.201602012]
[2]石满红,刘卫.基于非下采样剪切波变换域三变量模型图像去噪算法[J].红外技术,2017,39(11):1045.[doi:10.11846/j.issn.1001_8891.201711013]
 SHI Manhong,LIU Wei.Image Denoising Using a Trivariate Model in the Nonsubsampled Shearlet Transform Domain[J].Infrared Technology,2017,39(12):1045.[doi:10.11846/j.issn.1001_8891.201711013]
[3]葛 朋,杨 波,毛文彪,等. 基于引导滤波的高动态红外图像增强处理算法[J].红外技术,2017,39(12):1092.[doi:10.11846/j.issn.1001_8891.201712005]
 GE Peng,YANG Bo,MAO Wenbiao,et al. High Dynamic Range Infrared Image Enhancement Algorithm Based on Guided Image Filter [J].Infrared Technology,2017,39(12):1092.[doi:10.11846/j.issn.1001_8891.201712005]
[4]甘玲,张倩雯.结合NSCT与引导滤波的图像融合方法[J].红外技术,2018,40(5):444.[doi:10.11846/j.issn.1001_8891.201805007]
 GAN Ling,ZHANG Qianwen.Image Fusion Method Combining Non-subsampled Contourlet Transform and Guide Filtering[J].Infrared Technology,2018,40(12):444.[doi:10.11846/j.issn.1001_8891.201805007]

备注/Memo

备注/Memo:

收稿日期:2017-09-13;修订日期:2017-11-17.

作者简介:葛朋(1992-),男,硕士研究生,主要研究方向为红外图像处理技术。E-mail:542851112@qq.com。

通信作者:韩庆林(1965-),男,研究员级高级工程师,主要研究方向为混合信号集成电路设计。

更新日期/Last Update: 2018-12-19