一种结合 PE的高动态范围红外图像压缩及细节增强算法

葛朋; 杨波; 洪闻青; 王晓东; 刘传明; 苏兰; 苏俊波

红外技术, 2020, 42 (3): 279, 网络出版: 2020-04-13

一种结合 PE的高动态范围红外图像压缩及细节增强算法

Dynamic Range Compression and Detail Enhancement Algorithm Combined with PE for High Dynamic Range Infrared Images

论文大纲

葛朋杨波洪闻青王晓东刘传明苏兰苏俊波

作者单位

昆明物理研究所, 云南昆明 650223

引导滤波红外图像细节增强动态范围压缩平台直方图均衡 guided image filter, infrared image, detail enhanc

摘要

针对在提升高动态范围红外图像中潜在或弱小目标细节的同时, 还需兼顾噪声抑制、对比度增强的问题, 提出了一种基于引导滤波图像分层的动态范围及细节增强算法。对背景层采用平台直方图均衡算法进行压缩, 对细节层先采用中值滤波进行去噪, 再采用非线性映射对细节中潜在的弱小目标细节进行增强, 最后按照一定权重合并得到细节增强后的图像。综合主、客观实验结果, 相对于映射类、直方图均衡、双边滤波分层增强等算法, 该算法能够在动态范围压缩的过程中提高红外图像目标场景的对比度, 突显其纹理特征, 取得良好的细节增强效果。

Abstract

To address the problem of noise suppression and contrast enhancement in enhancing the details of potential or small targets in infrared images with a high dynamic range, a dynamic range and detail enhancement algorithm based on a guided filter image is proposed. The base layer is compressed by a plateau-histogram equalization algorithm. The detail layer is denoised by a median filter first, and then the potential and small target details are enhanced by nonlinear mapping. Finally, the image is integrated according to a certain weight to obtain the enhanced details. Based on the subjective and objective experimental results, compared with algorithms based on mapping, histogram equalization, and a bilateral filter, this algorithm can improve the contrast of the target scene of the infrared image in the process of dynamic range reduction. The proposed algorithm can highlight the texture features and obtain a good detail enhancement effect.

参考文献

[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. WEI Ruifeng, ZHAO Rongpu, XU Xiaoqing, et al. Infrared Image Detail Enhancement Based on Histogram[J]. Infrared Technology, 2016, 38(6): 472-475.

[2] VickersV. Plateau equalization algorithm for real-time display of high-quality infrared imagery[J]. Optical engineering, 1996, 35(7): 1921-1926.

[3] RezaA. Realization of the contrast limited adaptive histogram equalization (CLAHE) for real-time image enhancement[J]. The Journal of VLSI Signal Processing, 2004, 38(1): 35-44.

[4] Branchitta F, DianiM, CorsiniG, et al. New technique for the visualization of high dynamic range infrared images[J]. SPIE Optical Engineering,2009, 48(9): 76401-76414.

[5] ZUO C, CHEN Q, LIU N, et al. Display and detail enhancement for high-dynamic-range infrared images[J]. SPIE Optical Engineering, 2011, 50(12): 127401-127409.

[6] 杨静. 基于小波变换的低对比度图像增强方法 [J].计算机时代 , 2011(1): 10-12. YANG Jing. Approach of Low-contrast Image Enhancement Based on Wavelet Transform[J]. Infrared Technology, 2011(1): 10- 12.

[7] 朱道广, 隋修宝 , 朱才高 , 等. 基于多尺度的高动态红外图像增强算法[J].红外技术 , 2013, 35(8): 476-481. ZHU Daoguang, SUI Xiubao, ZHU Caigao, et al. Enhancement Algorithm for High Dynamic Range Infrared Image Based on Multi-scale Processing[J]. Infrared Technology, 2013, 35(8): 476-481.

[8] Rossi A, Acito N, Diani M, et al. High dynamic range compression for visualization of IR images in maritime scenarios[C]//SPIE Proceedings, 2012, 8451: 85410V1-85410V10.

[9] 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.

[10] LIU Ning, ZHAO Dongxue. Detail enhancement for high dynamic range infrared images based on guided image filter[J]. Infrared Physics and Technology, 2014, 67(7): 138-147.

葛朋, 杨波, 洪闻青, 王晓东, 刘传明, 苏兰, 苏俊波. 一种结合 PE的高动态范围红外图像压缩及细节增强算法[J]. 红外技术, 2020, 42(3): 279. GE Peng, YANG Bo, HONG Wenqing, WANG Xiaodong, LIU Chuanming, SU Lan, SU Junbo. Dynamic Range Compression and Detail Enhancement Algorithm Combined with PE for High Dynamic Range Infrared Images[J]. Infrared Technology, 2020, 42(3): 279.

一种结合 PE的高动态范围红外图像压缩及细节增强算法

关于本站 Cookie 的使用提示

全站搜索

一种结合 PE的高动态范围红外图像压缩及细节增强算法

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索