Study Of The Technology Of Denoising And Fusion About Remote Sensing Images

Remote Sensing is a new technology which is based on aero photographic methods since 1960s.As the carrier of remote sensing information, the remote sensing images ineluctably exists noise in the procedure of getting and transmitting. How to improve the images becomes the mainly task of the remote sensing processing. Meanwhile, because of the multi resolution analysis of the wavelet transform, it has been widely used in image processing, signal detection and so on. The paper studies the denoising and fusion about the remote sensing images with the wavelet transform.The paper systematically studies and summarizes about the relevant knowledge of remote sensing and wavelet transform, introducing characteristics of remote sensing image and relevant wavelet transform theory. The way to process the remote sensing images includes three parts which are denoising data in one dimensional, denoising the images in two dimensional, and image fusion. The paper mainly studies denoising data in one and two dimensional. In the procedure of the denoising in one dimensional, the paper processes data with white and colored noise separately. According to the characteristic of colored noise, based on the study of wavelet transform, the paper uses the way based on wavelet packet transform and robust estimation to removal colored noise meanwhile puts forward a new interval segmentation algorithm to processes data in sublevel, then making further study on two dimensional, and proposes an edge recovery method. The method combines traditional way, the wavelet analysis and edge detection. It could get the purpose of denoising the image and reservation the edge information.To improve the image quality, the paper fuses remote sensing denoised images, and uses the edge recovery way which is used in denoising about images in process in this paper. Meanwhile the paper researches the wavelet bases, threshold principle, and decomposition level in denoising in one and two dimensional and image fusion.The result shows that the methods which are proposed by this paper could effectively denoise the image and preserve the edge, getting better process effect and improving the quality of the image.