Block-regression based fusion of optical and SAR imagery for feature enhancement
This paper focuses on the establishment of a pixel-level fusion framework for optical and synthetic aperture radar (SAR) images to combine these two types of remotely sensed imagery for feature enhancement. We have proposed a new fusion technique, namely block-based synthetic variable ratio (Block-SVR), which is a technique based on multiple linear regression of block regions to fuse optical and SAR imagery. In order to investigate the effectiveness of the method, the fusion results of a higher resolution airborne SAR image and a lower resolution multispectral image are presented. According to the fusion results, the fused images have enhanced certain features, namely the spatial and textural content and features that are invisible in multispectral images, while preserving colour characteristics. The spectral, spatial and textural effects of the presented algorithm were also evaluated mainly by visual and quantitative methods, and compared to those of intensity-hue-saturation (IHS), principal component analysis (PCA) and wavelet-based methods. During the implementation of the block-regression based technique there are at least two advantages. One is that the block-regression based technique drastically decreases the amount of computation, whereas regression of the whole scene image is almost impossible. The other, most important, advantage is that adjustment of regressed block size can result in different emphasis between preservation of spectral characteristics and enhancement of spatial and textural content. The larger the regression block, the more the spatial and textural details are enhanced. In contrast, the smaller the regression block, the more the spectral features are preserved. The assessments indicate that the block-regression based method is more flexible than others, because it can achieve a satisfactory trade-off between preservation of spectral characteristics and enhancement of spatial and textural content by selection of optimal block size with respect to visual interpretation and mapping. This paper also proposes a scheme for the fusion of SPOT5 panchromatic, XS images with airborne SAR images using the block-regression based technique.
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Document Type: Research Article
Affiliations: Chinese Academy of Surveying and Mapping (CASM) 28 West Lianhuachi Street, Haidian, Beijing, PR, China
Publication date: 2010-03-01