| In recent years, multisensor image fusion has attracted many attentions in remote sensing area and image project area. This paper focuses on image fusion between multispectral images and panchromatic images. In order to enhance the result image's spatial resolution with preserving spectral information, research on algorithms is developed in next chapters.This dissertation firstly studies the cardinal concepts and theories of multisensor data fusion (information fusion). At the same time, this paper introduces steps and procedures of pretreatment in remote sensing image fusion. Afterwards, the paper systematically research the techniques used in pixel-level image fusion and four traditional algorithms (IHS, YIQ, PCA, HPF). Based on making out evaluation criteria of result image in impersonality and personality, merits and demerits of algorithms on multi-band image fusion are discussed. At the same time, HPF(high pass filter) method is compared with wavelet method among single-band image fusion methods. Author stresses the research on the details of algorithm based on wavelet transform, and gets such fresh ideas as:1. This paper puts forward a new measurement based on feature product. Feature product was defined with feature moments of the wavelet coefficients with high frequency component under different resolutions, based on transform of IHS and wavelet multiresolution analysis.2. Based on the measurement of feature product, a new idea that additive select fusion take the place of select fusion is introduced.3. According to the local feature product and the new idea ,a new pixel-level image fusion algorithm is produced.At last, computer simulations of image fusion are carried out by a group of multispectal images and panchromatic images. Compared with the result of IHS , HPF traditional fusion methods and the normalized correlation moment method, it is proved the validity of this method ,which can improve spatial resolution of the result images with preserving spectral information. |
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