This paper introduces the theory and method of image de-noising on wavelet threshold. On the basis of the traditional
threshold algorithm, a new improved algorithm which changes the threshold is put forward. And use the MATLAB to
achieve the remote sensing image de-noising. Experimental results show that the peak signal noise ratio (PSNR) of the
new threshold algorithm has improved significantly than the traditional threshold algorithm and lower mean square error
(MSE) significantly in Gaussian noise of remote sensing image de-noising. The de-noising effect is better.
Due to the kalman filter can achieve good results while dealing with dynamic data, and the deformation data has dynamic
characteristic, so in this paper, we use kalman filter to process data. In reality, the dynamic noise and observation noise are
unknown previously, we often set initial values of noise based on the former experiences, and thus the precision of standard
kalman filter will be effected by the inexact values of these two noise. However the innovation kalman filter could modify
the dynamic noise and observation noise continuously, in this paper, this algorithm has obtained good results in tunnel
deformation monitoring, and it has certain feasibility.
With the development of measurement technology, using the total station and GPS in the mining area are popular in the
mine ground and underground contact measurement. Due to the particularity of the mining area, sometimes the
measurement data of low precision can't meet the production requirements. In this paper using HAAR wavelet
processing the measured data of a certain coal mine ground and underground contact domestic. To the original data
preprocessing, first eliminate noise and then carries on the adjustment. After removed the noise of the late adjustment
data quality, is conducive to improve the quality of the final data, to meet actual production needs.
Proc. SPIE. 9808, International Conference on Intelligent Earth Observing and Applications 2015
KEYWORDS: Signal to noise ratio, Detection and tracking algorithms, Image processing, Digital filtering, Linear filtering, Image quality, Image filtering, Image denoising, Electronic filtering, Geomatics
Image noise is one of important factors that affects quality of image in the process of remote sensing imaging. So. the
image de-noising is a basic and key technology in the field of image processing. In this paper, the classical linear filtering,
such as arithmetic average filter, harmonic mean filter, and geometric mean filter , are applied to do the image de-noising
and the analysis for the characteristics of each de-noising method. The improvement scheme of the linear filtering which
based on the mean filtering is proposed by the way of adding the threshold, and the root mean square error (MSE) and
peak signal to noise ratio (PSNR) are used on its accuracy evaluation.