The echo signal of MIE scattering and polarization lidar is contanminated by the noises including background noises and detector noises, there exist obvious difference in fourier spectrums of original signals and denoised signals at high frequency parts. In this paper, a new method of lidar signal denoised by scattering wavelets was proposed, and original PRR signals of lidar were denoised by different wavelet basis. The experimental results showed that:1) Daubechies 4 wavelet basis (db4) met the requirements of denoising; 2)wavelet denoising could better preserve peak features of lidar echo signal than moving average method; 3) the original and detailed characteristics of atmospheric aerosol extinction profile was maintained, and the accuracy of atmospheric aerosol extinction coefficient inversion was improved. For lidar echo signals with low SNR, this method improved data processing method of Mie-scattering and polarization lidar and improved the accuracy of the retrieval of atmospheric aerosol extinction coefficient, the signal contamination from electric noise and the background light noise can be reduced by the proposed wavelet method.
Medical image processing has been investigated for more than three decades. It is clear that medical imaging will still
play a very dominant role in clinical research as well as in the daily routine practice in the coming decade. For a number
of reasons the images obtained by the medical instruments itself, such as CT, MRI are insufficient for the efficient
performance of a surgical intervention and various image processing techniques are necessary in order to make the most
important features more easily visible. Owing to its rapidly increasing popularity over last few decades, the wavelet
transform has become quite a standard tool in numerous image research and application domains. Wavelet thresholding
has been a popular technique for image denoising. The basic principle of wavelet thresholding is to identify and zero out
wavelet coefficients of a signal which are likely to contain mostly noise. By preserving the most significant coefficients,
wavelet thresholding preserves important highpass features of a signal such as discontinuities. Here we used this
technology in medicine image denoising and resulted in quite satisfying result. The goal of the medical image denoising
in a broad sense is the research, implementation, and validation of image processing approaches. Research is carried out
among others medical application areas.
Knowing the quantity of pollutants that the vehicle fleet is emitting to the air has become a vital question in almost every major city in China. Finding and fixing gross polluters is therefore very important to control the urban air quality and protect the human health and the environment. Remote sensing is an important advance in the technology of on-road vehicle emissions testing because it is fast, mobile, and unobtrusive. This on-road vehicle emissions remote system is designed to measure the carbon monoxide, carbon dioxide and opacity from the vehicles's tailpipe based on the Tuneable Diode Laser Absorption Spectroscopy (TDLAS). There are several advantages of this system such as compact design and ease of use. The measurement principle and optical layout of the instrument has been described in this paper. Field testing at Beijing and Hefei were conducted over one year, more than 6000 vehicles were tested. This vehicle emissions remote system has been shown to be able to measure CO,CO<sub>2</sub> and opacity from individual at highway speeds. In parallel, the plate license, speed, acceleration and length of vehicle are recognised by computer so that the owners of vehicles exceeding the permissible level of emissions can be identified.