像素级遥感影像融合方法研究
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摘要
遥感是上世纪50年代以后快速发展起来的一门科学技术,在获取地球有关信息时具有范围大、速度快、周期短、手段多样、信息量丰富等特点,已成为人类获取地球信息的主要手段,被广泛应用于环境、资源、海洋、地质、林业、农业及测绘等领域。遥感影像是传感器记录信息的主要形式,源于不同传感器和不同应用目的,在不同时期获取的遥感影像具有不同的光谱特性、空间分辨率。实际应用中,经常需要对不同波段、不同时间及不同空间分辨率的遥感影像予以融合,以获取观测对象更为全面和直观的信息,为决策提供更为有力的依据。本文主要对现阶段应用非常广泛的多光谱与全色影像、可见光影像与合成孔径雷达(Synthetic Aperture Radar, SAR)影像像素级融合中的一些问题展开研究,进而给出改进算法,主要创新有：
(1)在多光谱影像与全色影像融合中,IHS(Intensity-Hue-Saturation)变换融合法是一种重要的融合方法,已被集成到众多遥感影像处理软件中。但IHS变换融合法的融合结果相对于原多光谱影像光谱特性扭曲相当严重,研究人员对此进行了深入研究,提出了较多改进方案。本文详细分析了以往各种IHS变换融合法,认为光谱扭曲主要在于IHS变换后的I分量与全色影像差异过大引起的,考虑到以往方法并未曾考虑到卫星影像成像过程的复杂性(包含诸多不确定因素),提出采用统计方法确定变换中I分量计算的权值。仿真实验表明本文所提改进方法相对于以往IHS变换融合法,在不影响全色影像空间细节保持能力情况下,更好地保持了原多光谱影像的光谱特性。
(2)研究表明,Wavelet+IHS变换是多光谱影像与全色影像融合最为优异的方法之一,在应用小波变换时,一般认为观测目标的空间信息主要包含在小波分解后的高频分量,而多光谱影像的光谱信息包含在分解后的低频分量,融合策略主要是用全色影像的高频分量替换多光谱影像的高频分量,实现空间细节信息的注入,从而获取高空间分辨率的多光谱影像。通过对影像高频分量的观察,本文认为多光谱影像与全色影像均包含了观测目标的空间信息,只是精度不同,可以利用遥感影像自身携带的先验信息-空间分辨率比值做为影像观测精度比值,应用最小二乘原理得到空间细节信息的最优估计,以获取更为优质的融合影像。实验表明相对于前述融合方法,最优估计方法能够更好的集成多光谱影像的光谱信息和高空间分辨率全色影像的空间信息,可获得更为理想的高分辨率融合影像。在融合影像严格配准的情况下,本文提出的方法在空间细节方面获得了相对于真实地面情况的最优估计。
(3)由于遥感影像数据量巨大,融合方法的计算效率就显得至关重要。DCT(Discrete Cosine Transform)是傅立叶变换的一种特殊情形,其运算速度要高于小波变换,已被应用于多光谱影像与全色影像融合,但已有方法未能对融合模式进行深入分析,缺乏理论依据。本文结合遥感影像成像机理,提出将基于融合影像空间分辨率比值的影像分块模式结合DCT变换用于多光谱与全色影像融合。最终实验表明本文方法的光谱保持性能与小波变换方法持平,获得了理想的融合结果,运行效率也获得了提升。
(4)SAR影像与可见光影像是视觉效果完全不同的两类遥感影像,前者反映了地面目标对微波的后向散射特性,且具有全天时、全天候的观测能力,其携带的信息与后者形成了很好的互补关系。但SAR影像受斑点噪声影响,解译难度很大。为提高SAR影像解译水平,正确识别、分析目标,很有必要将它与符合人类视觉特性的多光谱影像进行融合。为避免基于小波变换的融合方法造成的SAR影像信息损失,本文提出一种基于atrous小波与广义IHS变换的SAR与多光谱影像融合方法,根据解译需要,通过改变阈值控制对多光谱影像信息的集成幅度。实验表明,本文所提出的方法可根据需要通过阈值调节多光谱影像信息的注入程度,同时完整地保留SAR影像信息,为不同解译需求提供不同的融合选择,而常规的小波融合结果仅为本文所给方法融合结果之一
(5)基于多尺度分析的遥感影像融合方法是近年来的研究热点,Contourlet变换是小波变换的再发展,它将小波变换在一维空间的良好特性扩展到二维空间,克服了小波在二维空间不能有效捕捉、表示线型空间实体的缺点,而将小波在一维空间的时频关系保持下来,具有良好的多分辨率、局部化及方向性特性,将其应用于影像融合,其在高频域将空间细节分解到各个方向,使得影像融合时会有更多的选择,融合效果将会更加细腻。为提高SAR影像解译能力,本文应用Contourlet+IHS变换融合SAR与多光谱影像,融合策略为低频域采用SAR影像系数,以保持SAR影像的光谱特性,高频域采用绝对值取大的原则,使得影像中能量较大的系数被选中,提高融合影像系数的差距,使影像更加清晰,结果表明,无论是目视比较还是统计分析,本文所给方法都很好地将SAR影像的空间细节与多光谱影像的色彩信息集成起来,显著地提高了SAR影像的解译水平,相对于IHS、DWT+IHS变换的融合方法获得了更好质量的融合影像。
Remote sensing is a technology that developed rapidly from the middle of last century. It has been widely used in environmental, atmospheric, resources, oceans, geology, agriculture, forestry and other fields because it has some observation features that range widely, speed quickly, period shortly, methods diversely and has clooected redundant information about the earth. Remote sensing images are the primary means to record information. For different reasons, human access to remote sensing images with different spectral bands, spatial resolution and time resolution, they are reflection of different characteristics of target observed. In practice, images with different spectral bands, spatial resolution and time obtained are often needed to be fused to produce more comprehensive, accurate information so as to provide a robust basis for decision-making. This dissertation mainly aims at the research of pixel level fusion methods of multi-spectral images and panchromatic image, visible images and synthetic aperture radar (Synthetic Aperture Radar, SAR) image, the main innovations of this dissertation are summarized as follows:
(1) For the fusion of multi-spectral images and panchromatic image, IHS (Hue-Intensity-Saturation) transform fusion method is an important method and has been integrated into a number of remote sensing image processing softwares. Studies show that the fusion method based on Wavelet+IHS transform is the one of best methods, but the fusion result of IHS transform consist of serious spectral distortion. The researchers have studied this problem deeply and proposed many measures to improve. This paper analyzes the various IHS transform fusion method previously and considers the spectrum distortion is caused by the large difference between I component of IHS transformed and the high resolution panchromatic image. It is taken into account that the previous method does not consider the complexity of satellite imaging and includes many uncertainties, using the statistical method to determine the transformation I calculate the weight of components are proposed here. Fusion result evaluation shows the proposed method could preserve spectral character better than previous IHS transform in the case of maintaining ability of integrate spatial details of panchromatic image. But compared to ideal images, fusion result still has some loss.
(2) During the fusing of multi-spectral images and panchromatic image, it is thought the spatial information of target observed is included in high frequency components of wavelet coefficients, while spectral information of target observed is contained in low frequency components of wavelet coefficients. The fusion strategy is the low frequency component of multi-spectral images is substituted by the high frequency component of panchromatic image to inject spatial details of panchromatic image and at last high spatial resolution multi-spectral images are produced. So we could utilize the least square principle to estimate the optimal value of spatial information to complete fusion making images'prior information-the ratio of spatial resolution as the ratio of the observation precision. Fusion result evaluation shows the proposed method could integrate spatial information of panchromatic image and spectral information of multi-spectral images better than other methods and produce more ideal high spatial resolution multispectral images.
(3) Since a huge amount of remote sensing data, the computational efficiency is particularly important for image fusion. DCT (Discrete Cosine Transform) is a special case of Fourier transform. The operation speed is higher than the wavelet transform and has been applied to multi-spectral image and panchromatic image fusion. However, integration of existing methods failed to conduct in-depth analysis model so as to it lack theoretical basis. In this paper, a new method is proposed based on the ratio of fusion image spatial resolution combined with DCT-block mode to fuse multi-spectral images and panchromatic image. Final results show that the abilities of spectral characters preserved of method proposed is as good as the method based on wavelet transform and ideal fusion result is obtained, but its operating efficiency is enhanced simultaneously.
(4) SAR image is different with visible light remote sensing image completely, reflecting the backscattering properties of ground target about microwave. SAR could observations earth in all-time, all-weather, penetrate clouds, rain, snow, fog and some Surface materials of earth, information of SAR image and visible light image are a kind of complementary relationship. Affected by speckle noises, the interpretation of SAR image is difficult, it is necessary to fuse SAR image and visual light image to hence SAR image's interpretation. To avoid loss of SAR image in previous fusion method based on wavelet transform. A new approach is proposed based on atrous wavelet and generalized IHS transform. It could control the amount of visual light image's information by changing the threshold value according to the need for interpretation. Experiments show that the method proposed could fuse SAR image and visual light image better than other method based on wavelet transform according different needs, and retains all information of SAR image. It has more freedom in practice.
(5) Remote sensing image fusion method based on multi-scale analysis is a research hotspot in recent years. Contourlet transform is further development of wavelet transform, it extends the good characteristics of wavelet from one-dimensional space to two-dimensional space, overcomes the shortcoming of wavelet in two-dimensional space that could not capture, represent linear spatial entities efficiently. Contourlet transform has good multi-resolution, localized and directional characteristics. There are more choices when Contourlet transform is used to fuse images, and the fusion results will be more delicate. To improve the ability of SAR image interpretation, the method based on Contourlet+IHS transform is proposed to fuse SAR image and multi-spectral images. The strategy is low frequency coefficients of SAR images is hold to maintain the spectral characteristics of SAR images, in high frequency domain, the coefficients of absolute maximum is selected to improve gap between SAR image's coefficient and multi-spectral coefficient, the fusion result will be more clear. The experiment results that are evaluated by visually and statistically shows that more successful results is achieved in the fusion of SAR and Multi-spectral images using the method proposed in this paper than methods based on IHS and DWT+IHS transform. The color information of multi-spectral images and the spatial details of SAR image are integrated very well, and the level of interpretation of sar image is increased significantly relative to original SAR image.
(1)在多光谱影像与全色影像融合中,IHS(Intensity-Hue-Saturation)变换融合法是一种重要的融合方法,已被集成到众多遥感影像处理软件中。但IHS变换融合法的融合结果相对于原多光谱影像光谱特性扭曲相当严重,研究人员对此进行了深入研究,提出了较多改进方案。本文详细分析了以往各种IHS变换融合法,认为光谱扭曲主要在于IHS变换后的I分量与全色影像差异过大引起的,考虑到以往方法并未曾考虑到卫星影像成像过程的复杂性(包含诸多不确定因素),提出采用统计方法确定变换中I分量计算的权值。仿真实验表明本文所提改进方法相对于以往IHS变换融合法,在不影响全色影像空间细节保持能力情况下,更好地保持了原多光谱影像的光谱特性。
(2)研究表明,Wavelet+IHS变换是多光谱影像与全色影像融合最为优异的方法之一,在应用小波变换时,一般认为观测目标的空间信息主要包含在小波分解后的高频分量,而多光谱影像的光谱信息包含在分解后的低频分量,融合策略主要是用全色影像的高频分量替换多光谱影像的高频分量,实现空间细节信息的注入,从而获取高空间分辨率的多光谱影像。通过对影像高频分量的观察,本文认为多光谱影像与全色影像均包含了观测目标的空间信息,只是精度不同,可以利用遥感影像自身携带的先验信息-空间分辨率比值做为影像观测精度比值,应用最小二乘原理得到空间细节信息的最优估计,以获取更为优质的融合影像。实验表明相对于前述融合方法,最优估计方法能够更好的集成多光谱影像的光谱信息和高空间分辨率全色影像的空间信息,可获得更为理想的高分辨率融合影像。在融合影像严格配准的情况下,本文提出的方法在空间细节方面获得了相对于真实地面情况的最优估计。
(3)由于遥感影像数据量巨大,融合方法的计算效率就显得至关重要。DCT(Discrete Cosine Transform)是傅立叶变换的一种特殊情形,其运算速度要高于小波变换,已被应用于多光谱影像与全色影像融合,但已有方法未能对融合模式进行深入分析,缺乏理论依据。本文结合遥感影像成像机理,提出将基于融合影像空间分辨率比值的影像分块模式结合DCT变换用于多光谱与全色影像融合。最终实验表明本文方法的光谱保持性能与小波变换方法持平,获得了理想的融合结果,运行效率也获得了提升。
(4)SAR影像与可见光影像是视觉效果完全不同的两类遥感影像,前者反映了地面目标对微波的后向散射特性,且具有全天时、全天候的观测能力,其携带的信息与后者形成了很好的互补关系。但SAR影像受斑点噪声影响,解译难度很大。为提高SAR影像解译水平,正确识别、分析目标,很有必要将它与符合人类视觉特性的多光谱影像进行融合。为避免基于小波变换的融合方法造成的SAR影像信息损失,本文提出一种基于atrous小波与广义IHS变换的SAR与多光谱影像融合方法,根据解译需要,通过改变阈值控制对多光谱影像信息的集成幅度。实验表明,本文所提出的方法可根据需要通过阈值调节多光谱影像信息的注入程度,同时完整地保留SAR影像信息,为不同解译需求提供不同的融合选择,而常规的小波融合结果仅为本文所给方法融合结果之一
(5)基于多尺度分析的遥感影像融合方法是近年来的研究热点,Contourlet变换是小波变换的再发展,它将小波变换在一维空间的良好特性扩展到二维空间,克服了小波在二维空间不能有效捕捉、表示线型空间实体的缺点,而将小波在一维空间的时频关系保持下来,具有良好的多分辨率、局部化及方向性特性,将其应用于影像融合,其在高频域将空间细节分解到各个方向,使得影像融合时会有更多的选择,融合效果将会更加细腻。为提高SAR影像解译能力,本文应用Contourlet+IHS变换融合SAR与多光谱影像,融合策略为低频域采用SAR影像系数,以保持SAR影像的光谱特性,高频域采用绝对值取大的原则,使得影像中能量较大的系数被选中,提高融合影像系数的差距,使影像更加清晰,结果表明,无论是目视比较还是统计分析,本文所给方法都很好地将SAR影像的空间细节与多光谱影像的色彩信息集成起来,显著地提高了SAR影像的解译水平,相对于IHS、DWT+IHS变换的融合方法获得了更好质量的融合影像。
Remote sensing is a technology that developed rapidly from the middle of last century. It has been widely used in environmental, atmospheric, resources, oceans, geology, agriculture, forestry and other fields because it has some observation features that range widely, speed quickly, period shortly, methods diversely and has clooected redundant information about the earth. Remote sensing images are the primary means to record information. For different reasons, human access to remote sensing images with different spectral bands, spatial resolution and time resolution, they are reflection of different characteristics of target observed. In practice, images with different spectral bands, spatial resolution and time obtained are often needed to be fused to produce more comprehensive, accurate information so as to provide a robust basis for decision-making. This dissertation mainly aims at the research of pixel level fusion methods of multi-spectral images and panchromatic image, visible images and synthetic aperture radar (Synthetic Aperture Radar, SAR) image, the main innovations of this dissertation are summarized as follows:
(1) For the fusion of multi-spectral images and panchromatic image, IHS (Hue-Intensity-Saturation) transform fusion method is an important method and has been integrated into a number of remote sensing image processing softwares. Studies show that the fusion method based on Wavelet+IHS transform is the one of best methods, but the fusion result of IHS transform consist of serious spectral distortion. The researchers have studied this problem deeply and proposed many measures to improve. This paper analyzes the various IHS transform fusion method previously and considers the spectrum distortion is caused by the large difference between I component of IHS transformed and the high resolution panchromatic image. It is taken into account that the previous method does not consider the complexity of satellite imaging and includes many uncertainties, using the statistical method to determine the transformation I calculate the weight of components are proposed here. Fusion result evaluation shows the proposed method could preserve spectral character better than previous IHS transform in the case of maintaining ability of integrate spatial details of panchromatic image. But compared to ideal images, fusion result still has some loss.
(2) During the fusing of multi-spectral images and panchromatic image, it is thought the spatial information of target observed is included in high frequency components of wavelet coefficients, while spectral information of target observed is contained in low frequency components of wavelet coefficients. The fusion strategy is the low frequency component of multi-spectral images is substituted by the high frequency component of panchromatic image to inject spatial details of panchromatic image and at last high spatial resolution multi-spectral images are produced. So we could utilize the least square principle to estimate the optimal value of spatial information to complete fusion making images'prior information-the ratio of spatial resolution as the ratio of the observation precision. Fusion result evaluation shows the proposed method could integrate spatial information of panchromatic image and spectral information of multi-spectral images better than other methods and produce more ideal high spatial resolution multispectral images.
(3) Since a huge amount of remote sensing data, the computational efficiency is particularly important for image fusion. DCT (Discrete Cosine Transform) is a special case of Fourier transform. The operation speed is higher than the wavelet transform and has been applied to multi-spectral image and panchromatic image fusion. However, integration of existing methods failed to conduct in-depth analysis model so as to it lack theoretical basis. In this paper, a new method is proposed based on the ratio of fusion image spatial resolution combined with DCT-block mode to fuse multi-spectral images and panchromatic image. Final results show that the abilities of spectral characters preserved of method proposed is as good as the method based on wavelet transform and ideal fusion result is obtained, but its operating efficiency is enhanced simultaneously.
(4) SAR image is different with visible light remote sensing image completely, reflecting the backscattering properties of ground target about microwave. SAR could observations earth in all-time, all-weather, penetrate clouds, rain, snow, fog and some Surface materials of earth, information of SAR image and visible light image are a kind of complementary relationship. Affected by speckle noises, the interpretation of SAR image is difficult, it is necessary to fuse SAR image and visual light image to hence SAR image's interpretation. To avoid loss of SAR image in previous fusion method based on wavelet transform. A new approach is proposed based on atrous wavelet and generalized IHS transform. It could control the amount of visual light image's information by changing the threshold value according to the need for interpretation. Experiments show that the method proposed could fuse SAR image and visual light image better than other method based on wavelet transform according different needs, and retains all information of SAR image. It has more freedom in practice.
(5) Remote sensing image fusion method based on multi-scale analysis is a research hotspot in recent years. Contourlet transform is further development of wavelet transform, it extends the good characteristics of wavelet from one-dimensional space to two-dimensional space, overcomes the shortcoming of wavelet in two-dimensional space that could not capture, represent linear spatial entities efficiently. Contourlet transform has good multi-resolution, localized and directional characteristics. There are more choices when Contourlet transform is used to fuse images, and the fusion results will be more delicate. To improve the ability of SAR image interpretation, the method based on Contourlet+IHS transform is proposed to fuse SAR image and multi-spectral images. The strategy is low frequency coefficients of SAR images is hold to maintain the spectral characteristics of SAR images, in high frequency domain, the coefficients of absolute maximum is selected to improve gap between SAR image's coefficient and multi-spectral coefficient, the fusion result will be more clear. The experiment results that are evaluated by visually and statistically shows that more successful results is achieved in the fusion of SAR and Multi-spectral images using the method proposed in this paper than methods based on IHS and DWT+IHS transform. The color information of multi-spectral images and the spatial details of SAR image are integrated very well, and the level of interpretation of sar image is increased significantly relative to original SAR image.
引文
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