Cao Haijie, Liu Ning, Xu ji, Peng Jie, Liu Yuxin. Infrared image adaptive inverse histogram enhancement technology[J]. Infrared and Laser Engineering, 2020, 49(4): 0426003-0426003-7. doi: 10.3788/IRLA202049.0426003
Citation:
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Cao Haijie, Liu Ning, Xu ji, Peng Jie, Liu Yuxin. Infrared image adaptive inverse histogram enhancement technology[J]. Infrared and Laser Engineering, 2020, 49(4): 0426003-0426003-7. doi: 10.3788/IRLA202049.0426003
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Infrared image adaptive inverse histogram enhancement technology
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College of Electronic and Optical Engineering & College of Microelectronic, Nanjing University of Posts And Telecommunications, Nanjing 210023, China
- Received Date: 2019-12-15
- Rev Recd Date:
2020-01-13
Available Online:
2020-01-09
- Publish Date:
2020-04-24
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Abstract
In infrared images, when the traditional histogram equalizes the image, the detail pixels are easily immerged by the background pixels, resulting in the image being too bright and too dark. Based on this situation, an adaptive inverse histogram equalization algorithm was proposed in this paper. The algorithm enhanced image details by inverse statistics, adaptive selection threshold and segmentation mapping. Compared with the traditional histogram equalization algorithm, the inverse histogram equalization algorithm significantly improve the image visual effect in different gray level distributions and enhance the details of different areas of the image to different degrees. Moreover, under the premise of achieving better image processing effects, this algorithm can still guarantee real-time performance and high efficiency by optimizing calculation methods, and is suitable for FPGA hardware transplantation.
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References
[1]
|
于天河, 戴景民. 结合人眼视觉特性的红外图像增强新技术[J]. 红外与激光工程, 2008, 37(6): 951−954. doi: 10.3969/j.issn.1007-2276.2008.06.003
Yu Tianhe, Dai Jingmin. New infrared image enhancement technology combining human visual characteristics [J]. Infrared and Laser Engineering, 2008, 37(6): 951−954. (in Chinese) doi: 10.3969/j.issn.1007-2276.2008.06.003 |
[2]
|
Gonzalez R C, Woods R E. Digital Image Processing[M].2nd ed. London: Prentice Hall, 2002. |
[3]
|
Kim Y T. Contrast enhancement using brightness preserving bi-histogram equalization [J]. IEEE Transactions on Consumer Electronics, 1997, 43(1): 1−8. doi: 10.1109/30.580378 |
[4]
|
Chen S D, Ramli A R. Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation [J]. IEEE Transactions on Consumer Electronics, 2003, 49(4): 1301−1309. doi: 10.1109/TCE.2003.1261233 |
[5]
|
Caselles V, Lisani J L, Morel J M, et al. Shape preserving local contrast enhancement[C]//International Conference on Image Processing. IEEE, 1997. |
[6]
|
Kim J Y, Kim L S, Hwang S H. An advanced contrast enhancement using partially overlapped sub-block histogram equalization[C]//IEEE International Symposium on Circuits & Systems,2002. |
[7]
|
汪子君, 邱俨睿, 杨宏霄, 等. 基于鲁棒Otsu的红外无损检测缺陷分割算法[J]. 红外与激光工程, 2019, 48(2): 0204004. doi: 10.3788/IRLA201948.0204004
Wang Zijun, Qiu Yanrui, Yang Hongxiao, et al. Robust Otsu based infrared nondestructive testing defect segmentation algorithm [J]. Infrared and Laser Engineering, 2019, 48(2): 0204004. (in Chinese) doi: 10.3788/IRLA201948.0204004 |
[8]
|
刘志才, 李志广. 红外热像仪图像处理技术综述[J]. 红外技术, 2000(6): 27−32.
Liu Zhicai, Li Zhiguang. Overview of image processing technology for infrared thermal imager [J]. Infrared Technology, 2000(6): 27−32. (in Chinese) |
[9]
|
金伟其, 刘斌, 范永杰, 等. 红外图像细节增强技术研究进展[J]. 红外与激光工程, 2011, 40(12): 2521−2527. doi: 10.3969/j.issn.1007-2276.2011.12.040
Jin Weiqi, Liu Bin, Fan Yongjie, et al. Research progress of infrared image detail enhancement technology [J]. Infrared and Laser Engineering, 2011, 40(12): 2521−2527. (in Chinese) doi: 10.3969/j.issn.1007-2276.2011.12.040 |
[10]
|
贾永红. 计算机图像处理与分析[M]. 武汉: 武汉大学出版社, 2001.(in Chinese)
Jia Yonghong. Computer Image Processing and Analysis[M]. Wuhan: Wuhan University Press, 2001. |
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