Infrared Image Enhancement Based on Adaptive Bilateral Filtering and Directional Gradient
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摘要: 为克服现有的红外图像增强方法存在欠增强、过增强以及对比度不高等缺陷，提出了自适应双边滤波与方向梯度的红外图像增强方法。对双边滤波进行改进，加权系数自适应于平滑区域和细节区域，以作为Retinex的中心环绕函数，将红外图像分解为基础层和细节层；用改进的平台直方图均衡化对基础层图像进行增强；提出一种方向梯度算子，用其提取细节层图像的梯度图，进而对细节层图像进行非线性的自适应边缘增强。实验结果表明，相对于部分现有的方法，本文方法能更有效地提升红外图像的亮度和对比度，增强图像的视觉效果更佳。Abstract: To overcome the defects of existing infrared image enhancement methods, such as under-enhancement, over-enhancement, and low contrast, an infrared image enhancement method based on adaptive bilateral filtering and directional gradient is proposed. The bilateral filter was improved, and its weighting coefficient is now adaptive to smooth and detailed regions. The improved bilateral filter is used as the central surround function of Retinex to decompose the infrared image into a base layer and a detail layer. Using improved platform histogram equalization, the base layer image is enhanced, and a directional gradient operator is proposed to extract the gradient image of the detail layer image to perform nonlinear adaptive edge enhancement on the detail-layer image. Experimental results show that, compared with existing methods, the proposed method can improve the brightness and contrast of infrared images more effectively. In addition, the visual effect of enhanced images using this method is better.
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图 1 标准双边滤波与改进的双边滤波的效果
Figure 1. Effect of bilateral filtering and improved bilateral filtering
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图 7 改进的双边滤波对三个场景的增强效果
Figure 7. Enhancement effect of improved bilateral filtering on three scenarios
表 1 各算法对三个场景图像增强的信息熵
Table 1 Information entropy of each algorithm for image enhancement of three scenes
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[1] 韦瑞峰, 赵荣普, 徐肖庆, 等. 基于直方图的红外图像细节增强算法研究[J]. 红外技术, 2016, 38(6): 472-475. http://hwjs.nvir.cn/article/id/hwjs201606005 WEI R, ZHAO R, XU X, et al. Infrared image detail enhancement based on histogram[J]. Infrared Technology, 2016, 38(6): 472-475. http://hwjs.nvir.cn/article/id/hwjs201606005
[2] WANG Y, WANG X, LI B, et al. Infrared image enhancement method for color transfer and contrast equalization in image registration[C]// Proceedings of the SPIE, 2017, 10462: 1046258.
[3] Chaudhury S, Roy A. Histogram equalization-a simple but efficient technique for image enhancement[J]. International Journal of Image, Graphics and Signal Processing, 2013, 5(10): 55-62. DOI: 10.5815/ijigsp.2013.10.07
[4] Aquino-Mori´nigo P, Lugo-Soli´s F, Pinto-Roa D, et al. Bi-histogram equalization using two plateau limits[J]. Signal, Image and Video Processing, 2017, 11(5): 857-864. DOI: 10.1007/s11760-016-1032-0
[5] Faraj N, Abood L. Contrast enhancement of infrared images using adaptive histogram equalization (AHE) with contrast limited adaptive histogram equalization[J]. Iraqi Journal of Physics, 2018, 16(37): 127-135. DOI: 10.30723/ijp.v16i37.84
[6] Ashiba M, Tolba M, El-Fishawy A, et al. Gamma correction enhancement of infrared night vision images using histogram processing[J]. Multimedia Tools & Applications, 2019, 78(19): 27771-27783.
[7] LIU C, SUI X, KUANG X, et al. Optimized contrast enhancement for infrared images based on global and local histogram specification[J]. Remote Sensing, 2019, 11(7): 849. DOI: 10.3390/rs11070849
[8] 吕侃徽, 张大兴. 基于自适应直方图均衡化耦合拉普拉斯变换的红外图像增强算法[J]. 光学技术, 2021, 47(6): 747-753. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJS202106018.htm LV K, ZHANG D. Infrared image enhancement algorithm based on adaptive histogram equalization coupled with Laplace transform[J]. Optical Technique, 2021, 47(6): 747-753. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJS202106018.htm
[9] LI Y, ZHANG Y, NIAN L, et al. Infrared image enhancement method based on scale varies Retinex theory[J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(1): 104-111. DOI: 10.3788/YJYXS20163101.0104
[10] CHEN J, YANG X, LU L, et al. A novel infrared image enhancement based on correlation measurement of visible image for urban traffic surveillance systems[J]. Journal of Intelligent Transportation Systems, 2020, 24(3): 290-303. DOI: 10.1080/15472450.2019.1642753
[11] 魏然然, 詹伟达, 朱德鹏, 等. 改进多尺度的Retinex红外图像增强[J]. 液晶与显示, 2021, 36(3): 465-474. https://www.cnki.com.cn/Article/CJFDTOTAL-YJYS202103014.htm WEI R, ZHAN W, ZHU D, et al. Improved multi-scale Retinex infrared image enhancement[J]. Chinese Journal of Liquid Crystals and Displays, 2021, 36(3): 465-474. https://www.cnki.com.cn/Article/CJFDTOTAL-YJYS202103014.htm
[12] LV J, DENG B, LU Y. A new detail enhancement method for high dynamic range infrared image[J]. Journal of Physics: Conference Series, 2019, 1237(3): 032060. DOI: 10.1088/1742-6596/1237/3/032060
[13] LI T, ZHAO J, WU X, et al. Infrared imaging enhancement through local window-based saliency extraction with spatial weight[J]. IET Image Processing, 2021, 15(12): 2910-2925. DOI: 10.1049/ipr2.12276
[14] CHEN J, ZHAN Y, CAO H. Adaptive sequentially weighted median filter for image highly corrupted by impulse noise [J]. IEEE Access, 2019, 7: 158545-158556. DOI: 10.1109/ACCESS.2019.2950348
[15] 凡遵林, 毕笃彦, 马时平, 等. 亮度保持和细节增强的红外图像增强方法[J]. 中南大学学报(自然科学版), 2016, 47(6): 1967-1972. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGD201606020.htm FAN Z, BI D, MA, et al. Method for infrared image with brightness preservation and detail enhancement[J]. Journal of Central South University (Science and Technology), 2016, 47(6): 1967-1972. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGD201606020.htm
[16] LI S, JIN W, LI L, et al. An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization[J]. Infrared Physics & Technology, 2018, 90: 164-174.
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