Research On Remote Sensing Image Denoising Algorithm Based On Massive Satellite Data

In recent years,China has launched a large number of satellites,including the Beidou navigation satellite and a variety of weather,resource exploration satellites,it is obvious that China's space remote sensing technology shows a considerable progress.With so many satellites in space,massive amounts of data are received daily from a variety of sensors.During the period of data collection and transmission,data will be more or less affected by many uncertainties and polluted with noises.Therefore,it is a widely concerned research topic to compress data before transmission and remove noise after receiving.The local timefrequency characteristics and multiresolution analysis of wavelet transform are preferable,they can effectively extract the important information from image datas,and wavelet transform is widely applied in the field of image processing.The main work of this thesis are how to remove the noises preferably from received images by wavelet transform and to find a better method of data compression for transmission.Various denoising methods based on wavelet transform were already presented.In consideration of the method of threshold denoising,the selections of threshold and its function were discussed,and an improved method was proposed.The feasibility and effectiveness of the method were verified by simulation.Then,the classical wavelet coding algorithm was analyzed.Aiming at the shortcoming that the SPIHT encoding needs large memory space and many unnecessary operations,an improved encoding algorithm was proposed also,which can reduce the need of storage space and save time in the coding process.