Remote Sensing Image Fusion And Applications

In recent years, image fusion has been an important and useful technique for image analysis and computer vision. Multi-sensor image fusion has attracted many attentions in remote sensing area. The aim of image fusion is to combine multiple source image data from various sensors intelligently and to obtain more detailed, complete description and decision than any of the individual source images. As a result of this processing, the fused image is more useful for human and machine perception or further image processing tasks such as object detection and recognition. In this dissertation, we focus on the techniques and applications of the multiple remote sensing image fusion. In this dissertation, an automated FFT-based technique is proposed for registration of remote sensing images having different spatial resolution and relative rotation and shift. The proposed method is an extension of the phase correlation technique. The main characteristic of the algorithm is to align two images automatically without requiring either control points or sensor's parameters. Fourier scaling properties and Fourier rotational properties are used to find scale and rotational movement by Log-polar coordinate transform. The phase correlation technique determines the transnational movement. Experimental results show that satisfactory effect has been obtained by applying our method. A pyramid approach for remote sensing image registration based on mutual information is presented. The image pyramid is obtained by using the wavelet transform. Coarse-to-fine multi-resolution search approaches have been proposed to increase accuracy and efficiency. An exhaustive search algorithm is applied at the coarsest level of the image pyramid. Registration at higher levels can be performed with the result at the pervious level serving as the initial condition. Our algorithm has been applied on remote sensing images. Main advantages and drawbacks of two registration methods mentioned above were analyzed. In order to save the computarional time and improve registration accuracy, a new coarse-to-fine hierarchical strategy for image registration based on the combination of FFT with mutual information approaches. Based on the comprehensive review and summarization of previous articles and researching achievements, basic concepts, levels, models, structures, techniques and applications of the multi-source remote sensing image data fusion, especially for pixel-based image fusion, are discussed. Furthermore, assessments of the image fusion performance are studied. Several evaluation criteria are presented in this dissertation. These evaluation criteria are classified according to condition and purpose. The methods of pixel-based remote sensing image fusion are analyzed and studied (including direct average method, HIS transformation, The Brovey method, PCA method and HPF method), these methods are compared qualitatively and quantitatively according to sharpness, information content, spatial resolution and preserving the spectral characters of source multi-spectral images and so on. We mainly studied and discussed multi-resolution image fusion approaches. These approaches are classified into two types: direction and no-direction multi-resolution analysis. For no-direction multi-resolution analysis, three pyramids are presented including laplacian pyramid, contrast pyramid and ratio pyramid. The decomposition, reconstruction, and image fusion based on these pyramids were introduced. The effects of the type of pyramid, the number of pyramid decomposition level, the scheme of fusion and the size of local region to the fusion result were investigated. Some important conclusions were drawn through a great deal experiments. For direction multi-resolution analysis, sensing image fusion techniques based on wavelet transform and direction gradient pyramid transform were proposed. Their characters, decomposition, reconstruction, and image fusion based on these two techniques were detailed. Furthermore, we investigate a pixel level image fusion algorithm based on a novel multi-resolution transform called steerable pyramid, which is both aliasing free and translation invariant. The characteristics of steerable pyramid and the scheme of image fusion by using steerable pyramid were discussed. We analyzed the effect of the number of orientation band-pass filters and the decomposition level to the fusion result. In order to resolve the problem of dim target detection, a novel approach based on image fusion and mathematical morphology was proposed. First, the original images were fusedusing steerable pyramid transform technique based on effective fusion scheme. The targets can be enhanced and clearer in fused image. Second, mathematical morphology method was applied to detect the target based on the fused image. The experimental results show that the effect of our method is satisfactory. A series of experiments on image registration, fusion, and object detection are given in this dissertation. We also got some worthy conclusions and put forward some new conceptions.