The Study Of Wavelet Packet Analysis For Denoising And The Application On GPS Data Process

The image is often corrupted by noise in its sample, acquisition or transmission, the noise is the main factor that influenced image quality and greatly affected to extract the information from it, therefore, denoising is a task of great antiquity.In recent years, the wavelet theory praised as "mathematical microscope" has been rapidly developed. For the characteristics of its low entropy, multi-analysis, relativity removal and flexible bases, the wavelet transform has been widely applied in the field of denoising. With the development of wavelet theory, the thought of the wavelet packet transform has appeared. The wavelet packet transform is more meticulous than the wavelet transform in analyzing signal unite time domain with frequency region. The method of signal denoising in wavelet packet transform is a hot spot problem in the study of science. This paper does deeply research on the methods of denoising in wavelet packet transform and apply in the denoising of GPS data. These work extends the applying domain of wavelet packet analysis, at the same time, it can improve the precision of the GPS orientation, deeply consummate wavelet packet analysis theory and strengthen the GPS data processing.The main works of the paper are as follows.(1) This dissertation introduces the history and the state of denoising in wavelet transform and GPS data processing. Meanwhile, it also analysis the noise error of GPS signal and it's characteristic in wavelet transform.(2) The article deeply studies the thresholding denosing methods in wavelet analysis and structures two new thresholding functions based on the classic method of the soft thresholding and hard thresholding functions and the method in article. The two functions can overcome the defect of classic methods and obtain the best result by selecting different parameter in different denoising signal. The numerical value experiment in the new functions by computer simulation are carried out, the different threshold methods are compared.(3) A novel adaptive thresholding quick and optimization in wavelet packet analysis is put forward. This method can get the threshold according to any node of each level. At the same time, the new function can reduce the calculation by the number of wavelet packet coefficient that after thresholding. We proved the superiority of this method by the GPS single de-noising of a city in Hebei.