Research On Image Fusion Using Multiscale Transform And Its Application

With the development of sensor technology that brings the abundance of image sources, multisensor image fusion technique has been attracting a large amount in a wide aritey of applications such as military target recognition, intelligent robot, remote sensing, medicine image processing, manufacturing etc. In the mean time, multisensor image fusion technique has been a research hotpot in such area as image understanding, computer vision and remote sensing and so on. The mainly goal of this dissertation is to research fusion methods for multisensor image in pixel-level under the guidance of multiscale analysis theory. The fused objects include remote sensing images, multifocus images, infrared and visible light images and medicine images.Firstly, this dissertation introduces the research background, the concept of the image multi-scale analysis, and the related concepts, development statue and applications of image fusion technology. Secondly, the dissertation reviews the existing multisensor image fusion methods, and summarizes the research works of domestic and foreign scholar for multisensor image fusion. It also classifies the image fusion methods in various ways and briefly analyses their advantages and disadvantages. Thirdly, the dissertation gives the image fusion principle based on multiscale transform and the existing related research works in detail. Furthermore, it gives the objective assessing indexes formula of fused image quality used in this dissertation. Finally, the dissertation mainly focuses on the research of multisensor image fusion methods based on multiscale transform, which include pyramid transform, wavelet transform, Curvelet transform and nonsubsampled Contourlet transform. By means of previous research works, it proposes several new fusion schemes and gives the function expression of fusion rules, respectively. To verify the fusion schemes, the experiments have done with remote sensing images, multifocus images, infrared and visible light images and medicine images.This dissertation studies the image fusion methods and some fused rules. The main contributions of this dissertation are summarized as follows:(1) According to the feature of visual contrast masking, a new fusion method using improved image contrast based on multiscale pyramid transform is presented, which has considered each decomposition coefficient and the mean of all in a local window. (2) By studying the correlation between neighborhood subband coefficients of the source images that is decomposed by wavelet transform, a new image fusion method is proposed by using neighborhood correlation coefficient and average gradient based on wavelet transform, which has better fusion result in some problems.(3) After studying the characteristics of fusion method based on principal component transform and wavelet transform respectively, an adaptive remote sensing image fusion method based on principal component transform combined with wavelet transform is proposed. The low frequency information of highresolution image is effectively injected into the fused image. The proposed method eliminates the blocking effect of fusion image based on wavelet transform. In addtion, the border of fused image is clear. When preserving spectral information; spatial detail information is also improved.(4) The wavelet transform could not obtain effectively the geometric features and the singularity of image, such as curves. It maybe affects the fused image and the fusion result. After studing Curvelet transform theory and according to the characteristics of Curvelet transform coefficient, an adaptive fusion method is presented to fuse remote sensing image based on first-generation Curvelet transform, which takes the weak edge of images into consideration. The fused image not only preserves spectral information of the original multispectral image well, but also enhances spatial detail information largely.(5) Curvelet transform depictures the curve singularity of image well, so the activity level of image texture could be reflected by the changes of Curvelet coefficient energy in different directions. Considering the each energy of Curvelet coefficient and the mean of all in a local window, a new image fusion method using improved energy contrast based on second-generation Curvelet transform is presented. For the fusion of multifocus images, the experimental results show highly correlated informations and small difference between the fused image and source images. Besides, the fused image prserves the features of source image well.(6) The spectrum information may be lossed using traditional IHS transform to combine remote sensing image, so a new image fusion method is proposed by using the second-generation Curvelet transform to improve IHS transform. Two different remote sensing images experiments and analysis show that the propsed fusion method takes advantage of the features of IHS transform and Curvelet transform, and is able to extract the feature of original remote sensing images effectively.(7) By studying the fusion method using coefficient injection for remote sensing images based on wavelet transform will be bring the problem that the panchromatic image features could mask some features contained initially in multispectral images, a a novel and effective fusion method with improved coefficients injection based on nonsubsampled Contourlet transform is proposed. The experiments show that the method is as much as possible to retain the spectral information of multispectral image and the detail information of highresolution image.Each image fusion method is correspondily experimented on in this dissertation. It analyse the performance of proposed fusion methods from the subjective and objective aspects of the fused image and obtained some valuable conclusions. Experimental results and analysis show that the proposed fusion method can realize the integration of multifocus image, infrared and visible light images, medicine images and remote sensing images. The proposed image fusion methods have important guiding significance to solve the image fusion problemt.