SAR图像去噪及多源遥感数据融合算法研究
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摘要
SAR图像斑点噪声的存在严重影响了图像的质量，必须在解译和分析前要对其进行去除；SAR图像和光学遥感图像所反映的地物信息差别很大，影像融合技术能综合二者信息，发挥出更大优势。本文针对以上两个方面，对SAR图像斑点噪声去除和多源遥感数据融合算法进行了研究。
1．SAR图像去噪算法研究。首先介绍了斑点噪声产生机理、模型和统计特征，对常用的图像滤波器进行了分析。针对斑点噪声的乘性模型特点，构造了一种基于小波分析的滤波器：对SAR图像进行对数变换，利用小波变换对对数图像进行滤波处理，再通过指数变换得到去噪图像。本文提出了一套比较完整的滤波器性能评价指标体系，并利用其对各种滤波器进行评价和比较。通过对JERS-1 SAR图像的各种滤波图像进行了目视评价和指标比较，得出如下结论: (1)各种空间滤波器受滤波窗口的影响很大，5×5大小的滤波窗口滤波效果较好；(2)对比各种常用的空间滤波器，增强的Frost滤波器、增强的Lee滤波器和Gamma-MAP滤波器在去噪和纹理、结构特征保持方面效果最好；(3)小波滤波方法在保持SAR图像纹理细节方面表现出了很好的优势，还有待进一步研究。
2．多源遥感数据融合。对多源遥感数据融合的理论和常用方法进行了回顾。提出了一种基于二进制小波分析的融合方法，对正交和双正交小波用于小波融合进行了详细分析，深入研究了小波基长度和小波变换分解层数对融合效果的影响。在提出了一套较完整的影像融合的评价指标体系后，利用各种融合方法进行了三种不同影像与TM影像间的融合试验：JERS-1 SAR图像与TM影像的融合；ERS-2 SAR图像与TM影像的融合；SPOT-5与TM影像的融合。利用评价指标体系对各种融合结果进行了评价和比较，结果表明：(1)对于SAR图像与TM多光谱影像融合，与传统的融合方法相比，小波融合方法不仅能很好地保持SAR图像的纹理、结构信息，而且在TM光谱特征保持方面优势明显；(2)小波融合方法可以根据不同应用要求选取不同的小波基和小波变换分解层数，从而调整融合结果中SAR图像信息和TM信息的分配，使用十分灵活；(3)对三种不同影像间的融合都取得了很好的效果，表明小波融合方法对不同数据的适应性很强。
SAR (synthetic aperture radar) images are seriously corrupted by speckle noise, so it is often necessary to enhance the image by speckle suppression before data can be interpreted and analyzed. SAR image carries information quite different from optical image; Image fusion can combine the two types of information together, making them more useful. Based on the above two points, algorithms research in speckle suppression and multi-source image fusion were chosen as the main topic in this paper.
1.Speckle noise suppression. The arising mechanism, model and statistical characteristics of speckle noise are described and the popular filters are analyzed. Based on the multiplicative speckle model, a new filtering algorithm based on wavelet transform was developed. First, the multiplicative speckle noise was changed by logarithmic transform into additive noise, which simplified the subsequent speckle suppression. The speckle suppression was carried out in the process of wavelet transform of the logarithmic transformed image. Then the filtered image was achieved by exponential transform. The new filter and some other popular filters have been applied to JERS-1 SAR image. An approach for quality assessment of the filtered images was proposed. After qualitative and quantitative assessment, some conclusions have been drawn:(1)Spatial filters are affected greatly by filtering window size, the size of 5×5 presents best result;(2) Enhanced Frost filter, Enhanced Lee filter and Gamma-MAP filter smooth the speckle noise well with a small sacrifice of losing texture details and narrow edges, which are better than other popular spatial filters;(3) The results show that the proposed filter retains texture and edges well, so more researches are expected.
2.Data fusion. After the theories and popular algorithms were reviewed, a new algorithm based on wavelet transform has been proposed and deep research has been carried out to study the impact of the wavelet bases and decomposition levels on the fusion results. After presenting a set of indexes for fusion quality assessment, different fusion algorithms have been applied to three couples of images: JERS-1 SAR image with TM image; ERS-2 SAR image with TM image; SPOT-5 panchromatic image with TM image. With the fusion results been evaluated and compared by the quality assessment indexes presented in this paper, some conclusions have been drawn:(1) For the fusion of SAR image and TM image, compared with the traditional algorithms, the new algorithm based on wavelet transform retains SAR image's texture and structural information well, and its ability to preserve TM image's spectral information is far better than other algorithms;(2)
The new algorithm is very flexible due to its various choices of wavelet bases and decomposition levels according to certain applications.(3)Satisfactory results have been achieved by fusing three different types of images with TM image using the new algorithm, which shows that the new algorithm is well adaptive to different types of image data.
1．SAR图像去噪算法研究。首先介绍了斑点噪声产生机理、模型和统计特征，对常用的图像滤波器进行了分析。针对斑点噪声的乘性模型特点，构造了一种基于小波分析的滤波器：对SAR图像进行对数变换，利用小波变换对对数图像进行滤波处理，再通过指数变换得到去噪图像。本文提出了一套比较完整的滤波器性能评价指标体系，并利用其对各种滤波器进行评价和比较。通过对JERS-1 SAR图像的各种滤波图像进行了目视评价和指标比较，得出如下结论: (1)各种空间滤波器受滤波窗口的影响很大，5×5大小的滤波窗口滤波效果较好；(2)对比各种常用的空间滤波器，增强的Frost滤波器、增强的Lee滤波器和Gamma-MAP滤波器在去噪和纹理、结构特征保持方面效果最好；(3)小波滤波方法在保持SAR图像纹理细节方面表现出了很好的优势，还有待进一步研究。
2．多源遥感数据融合。对多源遥感数据融合的理论和常用方法进行了回顾。提出了一种基于二进制小波分析的融合方法，对正交和双正交小波用于小波融合进行了详细分析，深入研究了小波基长度和小波变换分解层数对融合效果的影响。在提出了一套较完整的影像融合的评价指标体系后，利用各种融合方法进行了三种不同影像与TM影像间的融合试验：JERS-1 SAR图像与TM影像的融合；ERS-2 SAR图像与TM影像的融合；SPOT-5与TM影像的融合。利用评价指标体系对各种融合结果进行了评价和比较，结果表明：(1)对于SAR图像与TM多光谱影像融合，与传统的融合方法相比，小波融合方法不仅能很好地保持SAR图像的纹理、结构信息，而且在TM光谱特征保持方面优势明显；(2)小波融合方法可以根据不同应用要求选取不同的小波基和小波变换分解层数，从而调整融合结果中SAR图像信息和TM信息的分配，使用十分灵活；(3)对三种不同影像间的融合都取得了很好的效果，表明小波融合方法对不同数据的适应性很强。
SAR (synthetic aperture radar) images are seriously corrupted by speckle noise, so it is often necessary to enhance the image by speckle suppression before data can be interpreted and analyzed. SAR image carries information quite different from optical image; Image fusion can combine the two types of information together, making them more useful. Based on the above two points, algorithms research in speckle suppression and multi-source image fusion were chosen as the main topic in this paper.
1.Speckle noise suppression. The arising mechanism, model and statistical characteristics of speckle noise are described and the popular filters are analyzed. Based on the multiplicative speckle model, a new filtering algorithm based on wavelet transform was developed. First, the multiplicative speckle noise was changed by logarithmic transform into additive noise, which simplified the subsequent speckle suppression. The speckle suppression was carried out in the process of wavelet transform of the logarithmic transformed image. Then the filtered image was achieved by exponential transform. The new filter and some other popular filters have been applied to JERS-1 SAR image. An approach for quality assessment of the filtered images was proposed. After qualitative and quantitative assessment, some conclusions have been drawn:(1)Spatial filters are affected greatly by filtering window size, the size of 5×5 presents best result;(2) Enhanced Frost filter, Enhanced Lee filter and Gamma-MAP filter smooth the speckle noise well with a small sacrifice of losing texture details and narrow edges, which are better than other popular spatial filters;(3) The results show that the proposed filter retains texture and edges well, so more researches are expected.
2.Data fusion. After the theories and popular algorithms were reviewed, a new algorithm based on wavelet transform has been proposed and deep research has been carried out to study the impact of the wavelet bases and decomposition levels on the fusion results. After presenting a set of indexes for fusion quality assessment, different fusion algorithms have been applied to three couples of images: JERS-1 SAR image with TM image; ERS-2 SAR image with TM image; SPOT-5 panchromatic image with TM image. With the fusion results been evaluated and compared by the quality assessment indexes presented in this paper, some conclusions have been drawn:(1) For the fusion of SAR image and TM image, compared with the traditional algorithms, the new algorithm based on wavelet transform retains SAR image's texture and structural information well, and its ability to preserve TM image's spectral information is far better than other algorithms;(2)
The new algorithm is very flexible due to its various choices of wavelet bases and decomposition levels according to certain applications.(3)Satisfactory results have been achieved by fusing three different types of images with TM image using the new algorithm, which shows that the new algorithm is well adaptive to different types of image data.
引文
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