基于多尺度的高动态红外图像增强算法
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摘要
红外图像通常具有很高的动态范围,数字量化位数一般大于或等于14 bit,这样的高动态图像既包含大的信号变量也包含较小的低对比度细节,这对于人眼的理解和显示设备的渲染都是不能接受的。在多尺度和边缘保留型滤波器的框架下,提出了一种改进的红外图像增强算法。首先是应用加权最小二乘滤波器对原始图像进行边缘保留式的图像多尺度分层操作,然后分别对得到的多层细节图像和残留模糊图像进行处理,使细节得到适当的放大,而残留层得到压缩,最后再把细节层和残留层合并,得到最终用于显示的低动态范围图像。该方法可以较好的保留红外图像细节,同时避免或削弱由细节分离操作所带来的合成图像中的光晕和梯度反转现象。
Infrared images usually have very high dynamic range(HDR),up to 14 digital bits or more,such high dynamic range image contains both large signal variations and small low contrast details,however,this is unacceptable for both human perception and the ability of display devices.In this paper,we propose an improved method for the enhancement of infrared images based on the framework of edge preserving filter and multi-scale processing.First,a weighted least square(WLS) filter is used to split the raw image into multi-scale layers.Then the detail layers and the coarse layer are processed separately,boosting the details properly and compressing the coarse layer accordingly.Finally,all the layers are recombined to get the low dynamic range image for display.We demonstrate that the method proposed can both preserve the details of infrared images and eliminate or weaken the artifacts of halo and gradient reversal.
Infrared images usually have very high dynamic range(HDR),up to 14 digital bits or more,such high dynamic range image contains both large signal variations and small low contrast details,however,this is unacceptable for both human perception and the ability of display devices.In this paper,we propose an improved method for the enhancement of infrared images based on the framework of edge preserving filter and multi-scale processing.First,a weighted least square(WLS) filter is used to split the raw image into multi-scale layers.Then the detail layers and the coarse layer are processed separately,boosting the details properly and compressing the coarse layer accordingly.Finally,all the layers are recombined to get the low dynamic range image for display.We demonstrate that the method proposed can both preserve the details of infrared images and eliminate or weaken the artifacts of halo and gradient reversal.
引文
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[9]王炳健,刘上乾,周慧鑫,等.基于平台直方图的红外图像自适应增强算法[J].光子学报,2005,34(2):299-301.
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[11]周妮,张湧,吴滢跃.一种新的实时红外图像增强技术[J].红外技术,2010,32(6):324-327.
[12]魏新,马丽华,李云霞,等.基于图像分割和平台直方图均衡的红外图像增强算法[J].红外技术,2012,34(5):272-275.
[2]Farbman Zeev,Fattal Raanan,Lischinski Dani,Szeliski Richard.Edge-Preserving Decompositions for Multi-Scale Tone and Detail Manipulation[J].ACM Transactions on Graphics,2008,27(3):67.
[3]Branchitta Francesco,Diani Marco,Corsini Giovanni,et al.New technique for the visualization of high dynamic range infrared images[J].Optical Engineering,2009,48(9):096401.
[4]Chao Zuo,Qian Chen,Ning Liu,et al.Display and detail enhancement for high-dynamic-range infrared images[J].Optical Engineering,2011,50(12):127401(9).
[5]Branchitta Francesco,Diani Marco,Corsini Giovanni,et al.Dynamic-range compression and contrast enhancement in infrared imaging systems[J].Optical Engineering,2008,47(7):076401-1-14.
[6]Elad Michael.On the origin of the bilateral filter and ways to improve it[J].IEEE Transactions on Image Processing,2002,11(10):1141-1151.
[7]Barash,Danny.A fundamental relationship between bilateral filtering,adaptive smoothing,and the nonlinear diffusion equation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(6):844-847.
[8]Lai Rui,Yang Yin-Tang,Wang Bing-Jian,Zhou Hui-Xin.A quantitative measure based infrared image enhancement algorithm using plateau histogram[J].Optics Communications,2010,283(21):4283-4288.
[9]王炳健,刘上乾,周慧鑫,等.基于平台直方图的红外图像自适应增强算法[J].光子学报,2005,34(2):299-301.
[10]Rafael C Gonzalez,Richard E Woods.Digital Image Processing[M]3rd Edition.北京:电子工业出版社,2003.
[11]周妮,张湧,吴滢跃.一种新的实时红外图像增强技术[J].红外技术,2010,32(6):324-327.
[12]魏新,马丽华,李云霞,等.基于图像分割和平台直方图均衡的红外图像增强算法[J].红外技术,2012,34(5):272-275.