双色中波红外图像差异特征分析及融合方法研究
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摘要
红外中波细分是多色化探测的重要组成部分，其成像在军事和民用领域都具有重要应用价值。探测中利用双色中波成像仪虽然能够采集到高质量且各具优势的两个细分波段图像，但是还需融合处理才能最终获取到更丰富、精确和可靠的目标信息。目前双色中波红外图像融合一般仅根据先验估计进行研究，由于未结合成像差异特性的深入分析，常常会造成无法针对性地选择和研究融合算法，从而严重制约了融合效果和效率的提升。针对该问题，本文从双色中波红外图像差异特征形成机理入手来研究其图像融合方法。
本文的主要研究内容包括以下三部分：
1、建立了两个细分中波段成像的差异特性形成模型。图像融合的目的是综合原图像的差异信息。而原图像的差异信息是在成像过程中形成的，是影响成像的各种因素的综合反映。一旦成像特性差异发生变化，通常图像的差异特征也随之改变，对融合方法的需求相应地也会发生变化。本文通过深入分析两个细分中波段的目标辐射特性、辐射传输特性、环境影响特性、探测器响应特性等成像因素来研究成像差异特性的形成机理。建立了红外点目标、面目标和大目标的成像演化模型；通过对模型仿真验证，揭示了两个细分中波段成像在灰度值和目标背景对比度方面的差异规律，为图像差异特征提取和融合规则制定提供了指导。
2、深入分析了两个细分中波段图像的差异特征。融合算法只有满足图像间差异特征的融合需求，冰能形成一幅数据质量更高、更适合人眼视觉观察的图像，因而，差异特征的提取和表征对图像融合研究具有决定性作用。本文分析了成像特性差异与图像特征差异的映射关系，以此为指导提取了两个细分中波段图像的视觉特征、统计特征、变，换域特征和代数特征，并且利用局部线性嵌入法、雷达图法、主分量分析法和分形维特征提取法等对差异特征进行了降维综合，得到了两个细分中波段图像的综合差异特征，据此确定了不同条件下成像的不同融合技术需求，为图像融合研究奠定了基础。
3、提出了针对不同成像条件的双色中波红外图像融合方法，均得到了能综合两个细分中波段原图像信息、并且更适合人眼视觉观察的融合图像。具体如下：
(1)通过建立两个细分中波段图像差异特征和融合策略之间的映射关系，为融合方法研究奠定基础。以所建立的映射关系为指导，在灰度图像融合中，针对阳光照射条件下的成像，提出了分割支持度变换融合方法；针对非阳光照射条件下的成像，提出了双树复小波与可能性映射相结合的融合方法。实验证明这两种方法的融合结果不仅图像细节更清楚、信息更丰富，而且运行速度都较快，有助于后续的融合自动化和工程化研究。在此基础上提出了基于阈上随机共振的双色中波红外弱信号图像融合方法，解决了强噪声情况下双色中波红外探测图像的融合问题。
(2)为了使融合图像更符合人的视觉特性，在灰度融合研究的基础上，采用伪彩色技术和颜色迁移技术对双色中波红外图像进行了彩色融合。在伪彩色融合研究中提出了“局部融合与全局融合相结合，先灰度融合、再彩色融合”的融合思路，并将FC^C#颜色空间映射与支持度变换灰度融合相结合实现了伪彩色融合。在颜色迁移融合中，提出了在颜色空间利用MWIR1和MWIR2-MWIR1图像的散度信息分别增强f/、V通道来提高融合效果的新方法。对仿真结果的主观和客观评价都表明：采用所提出方法融合的图像不仅清晰度更高、信息量更大、细节更清楚，而且更符合人的视觉特性，有助于场景的识别与理解。
Infrared mid-wave sub-band is an important part in multi-color detection. Its images playa very important role both in military and civil fields. By using a dual-color mid-wave imager,two sub-bands images, which are in high quality and have their own advantages, can becollected，but their plenty, accuracy, and reliable target information can be finally got only byfusion. Presently, the researches for dual-color mid-wave image fusion are done usually byprevious assessments. As some fusion algorithms can not be done without some relatedchoices and researches, the improvement of fusion result and efficiency can not be got. Thepaper here is directed to the problem mentioned. It starts with the formation ways of imagedifference characteristics in order to study the fusion ways of the dual-color mid-waveinfrared images.
There are mainly three parts in this paper.
1. Formation models have been built for the characteristic differences between twosub-bands. The purpose of image fusion is to synthesize the difference information of originalimages. The difference information is an aggregative reflection of various factors which isformed during detecting. Once the imaging characteristic differences change, the image'sdifference characteristics change accordingly, and the same is fusion needs. By deeplyanalyzing the imaging factors in the sub-bands such as radiance, radiance transmission,environment inlfuence, detector response, and so on, the paper tries to research the principlesof imaging difference characteristics. Besides, the imaging evolution models for the infraredpoint target, surface target, and the big target are also built here. The validity of these modelsproposed is proved by the simulation results. The difference rules between the gray scale andthe target background contrast degree for the two sub-band imaging are also brought out,'which produces some instructions for extracting images difference characteristics and making some fusion rules.
2. A deep analysis for the difference characteristics between the two sub-bands isshown in this paper. The fusing algorithm should meet the fusion demands of differencecharacteristics among images, then the images, which are both in high quality and ift topeople's vision, can be formed. So collecting and characterizing difference characteristics isvery important for the research of image fusion. Based on the mapping relations betweeni'maging characteristic differences and image characteristic ones, the images characteristics instatistics, vision, exchange and algebra are shown in the sub-bands. In addition, somemethods such as locally linear embedding(LLE)，radar chart, principal component analysis(PCA)，fractal dimension are used in order to lower the dimension. Then, the image'ssynthetic difference characteristics in the two sub-bands can be shown, which not onlydetermines different fusion technology demands in different imaging conditions，but also laysthe foundation for the study of image fusion.
3. Several fusion methods used for dual-color mid-wave infrared images are putforward in this paper，and some fusion images have been got from these methods. Theseimages can show synthetic information from the original images in the two mid-wavesub-bands, and they are more convenient for people to observe them.
By setting up the mapping relations between image difference characteristics and fusionstrategies, the foundation for studying the fusion ways is set up. Under the direction of thesemapping relations, two groups of fusion ways are put forward here.
(1)One group is for gray image fusion, which includes three ways. The ifrst one is thefusion of segmentation and support value transform, aiming at those images taken under thesun. The second one is the way to combine the dual-tree complex wavelet transform withpossible mapping，aiming at those images taken without the sunlight. The experimental resultsshow that fused images full of information and details. What is more，the operation speed ofthese fusion methods is much faster, which is very helpful to the latter study for fusionautomation and engineering. The last one in this group is the fusion for those dual-colormid-wave infrared weak signal images on the basis of supra-threshold stochastic resonance.The problem of strong noisy images fusion is solved.
(2)The other group of fusion methods is for the color fusion of the dual-color mid-waveinfrared images by using two ways of pseudo-color and color transfer. The pseudo-colorfusion is to combine the local fusion with overall fusion, and to do the gray fusion ifrst, then the color fusion. The pseudo-color fusion can be completed by combining gray fusion basedon support value transform with YCaCp color space mapping. The other way is for colortransfer fusion which is done by using the divergence from both the MWIR1andMWIR2-MWIR1images to increase the U passage and V passage separately, and then, toimprove the fusion result. Some experiments have proved that both subjective evaluation andobjective evaluation for the two fusion methods mentioned above are much better，fusionimages not only have higher resolution, more information and more clearly details, but alsomore closely ift with human perception. The fusion results are helpful to image identificationand understanding, which indicates that the fusion results are significant.
本文的主要研究内容包括以下三部分：
1、建立了两个细分中波段成像的差异特性形成模型。图像融合的目的是综合原图像的差异信息。而原图像的差异信息是在成像过程中形成的，是影响成像的各种因素的综合反映。一旦成像特性差异发生变化，通常图像的差异特征也随之改变，对融合方法的需求相应地也会发生变化。本文通过深入分析两个细分中波段的目标辐射特性、辐射传输特性、环境影响特性、探测器响应特性等成像因素来研究成像差异特性的形成机理。建立了红外点目标、面目标和大目标的成像演化模型；通过对模型仿真验证，揭示了两个细分中波段成像在灰度值和目标背景对比度方面的差异规律，为图像差异特征提取和融合规则制定提供了指导。
2、深入分析了两个细分中波段图像的差异特征。融合算法只有满足图像间差异特征的融合需求，冰能形成一幅数据质量更高、更适合人眼视觉观察的图像，因而，差异特征的提取和表征对图像融合研究具有决定性作用。本文分析了成像特性差异与图像特征差异的映射关系，以此为指导提取了两个细分中波段图像的视觉特征、统计特征、变，换域特征和代数特征，并且利用局部线性嵌入法、雷达图法、主分量分析法和分形维特征提取法等对差异特征进行了降维综合，得到了两个细分中波段图像的综合差异特征，据此确定了不同条件下成像的不同融合技术需求，为图像融合研究奠定了基础。
3、提出了针对不同成像条件的双色中波红外图像融合方法，均得到了能综合两个细分中波段原图像信息、并且更适合人眼视觉观察的融合图像。具体如下：
(1)通过建立两个细分中波段图像差异特征和融合策略之间的映射关系，为融合方法研究奠定基础。以所建立的映射关系为指导，在灰度图像融合中，针对阳光照射条件下的成像，提出了分割支持度变换融合方法；针对非阳光照射条件下的成像，提出了双树复小波与可能性映射相结合的融合方法。实验证明这两种方法的融合结果不仅图像细节更清楚、信息更丰富，而且运行速度都较快，有助于后续的融合自动化和工程化研究。在此基础上提出了基于阈上随机共振的双色中波红外弱信号图像融合方法，解决了强噪声情况下双色中波红外探测图像的融合问题。
(2)为了使融合图像更符合人的视觉特性，在灰度融合研究的基础上，采用伪彩色技术和颜色迁移技术对双色中波红外图像进行了彩色融合。在伪彩色融合研究中提出了“局部融合与全局融合相结合，先灰度融合、再彩色融合”的融合思路，并将FC^C#颜色空间映射与支持度变换灰度融合相结合实现了伪彩色融合。在颜色迁移融合中，提出了在颜色空间利用MWIR1和MWIR2-MWIR1图像的散度信息分别增强f/、V通道来提高融合效果的新方法。对仿真结果的主观和客观评价都表明：采用所提出方法融合的图像不仅清晰度更高、信息量更大、细节更清楚，而且更符合人的视觉特性，有助于场景的识别与理解。
Infrared mid-wave sub-band is an important part in multi-color detection. Its images playa very important role both in military and civil fields. By using a dual-color mid-wave imager,two sub-bands images, which are in high quality and have their own advantages, can becollected，but their plenty, accuracy, and reliable target information can be finally got only byfusion. Presently, the researches for dual-color mid-wave image fusion are done usually byprevious assessments. As some fusion algorithms can not be done without some relatedchoices and researches, the improvement of fusion result and efficiency can not be got. Thepaper here is directed to the problem mentioned. It starts with the formation ways of imagedifference characteristics in order to study the fusion ways of the dual-color mid-waveinfrared images.
There are mainly three parts in this paper.
1. Formation models have been built for the characteristic differences between twosub-bands. The purpose of image fusion is to synthesize the difference information of originalimages. The difference information is an aggregative reflection of various factors which isformed during detecting. Once the imaging characteristic differences change, the image'sdifference characteristics change accordingly, and the same is fusion needs. By deeplyanalyzing the imaging factors in the sub-bands such as radiance, radiance transmission,environment inlfuence, detector response, and so on, the paper tries to research the principlesof imaging difference characteristics. Besides, the imaging evolution models for the infraredpoint target, surface target, and the big target are also built here. The validity of these modelsproposed is proved by the simulation results. The difference rules between the gray scale andthe target background contrast degree for the two sub-band imaging are also brought out,'which produces some instructions for extracting images difference characteristics and making some fusion rules.
2. A deep analysis for the difference characteristics between the two sub-bands isshown in this paper. The fusing algorithm should meet the fusion demands of differencecharacteristics among images, then the images, which are both in high quality and ift topeople's vision, can be formed. So collecting and characterizing difference characteristics isvery important for the research of image fusion. Based on the mapping relations betweeni'maging characteristic differences and image characteristic ones, the images characteristics instatistics, vision, exchange and algebra are shown in the sub-bands. In addition, somemethods such as locally linear embedding(LLE)，radar chart, principal component analysis(PCA)，fractal dimension are used in order to lower the dimension. Then, the image'ssynthetic difference characteristics in the two sub-bands can be shown, which not onlydetermines different fusion technology demands in different imaging conditions，but also laysthe foundation for the study of image fusion.
3. Several fusion methods used for dual-color mid-wave infrared images are putforward in this paper，and some fusion images have been got from these methods. Theseimages can show synthetic information from the original images in the two mid-wavesub-bands, and they are more convenient for people to observe them.
By setting up the mapping relations between image difference characteristics and fusionstrategies, the foundation for studying the fusion ways is set up. Under the direction of thesemapping relations, two groups of fusion ways are put forward here.
(1)One group is for gray image fusion, which includes three ways. The ifrst one is thefusion of segmentation and support value transform, aiming at those images taken under thesun. The second one is the way to combine the dual-tree complex wavelet transform withpossible mapping，aiming at those images taken without the sunlight. The experimental resultsshow that fused images full of information and details. What is more，the operation speed ofthese fusion methods is much faster, which is very helpful to the latter study for fusionautomation and engineering. The last one in this group is the fusion for those dual-colormid-wave infrared weak signal images on the basis of supra-threshold stochastic resonance.The problem of strong noisy images fusion is solved.
(2)The other group of fusion methods is for the color fusion of the dual-color mid-waveinfrared images by using two ways of pseudo-color and color transfer. The pseudo-colorfusion is to combine the local fusion with overall fusion, and to do the gray fusion ifrst, then the color fusion. The pseudo-color fusion can be completed by combining gray fusion basedon support value transform with YCaCp color space mapping. The other way is for colortransfer fusion which is done by using the divergence from both the MWIR1andMWIR2-MWIR1images to increase the U passage and V passage separately, and then, toimprove the fusion result. Some experiments have proved that both subjective evaluation andobjective evaluation for the two fusion methods mentioned above are much better，fusionimages not only have higher resolution, more information and more clearly details, but alsomore closely ift with human perception. The fusion results are helpful to image identificationand understanding, which indicates that the fusion results are significant.
引文
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