Papers by Keyword: Wiener Filter

Abstract: Ship internal equipment vibration will cause the imaging system platform vibration, resulting in blurred images. Wiener Filter is often used to restore the motion blurred image. The principle of the method expects to minimize the mean square error between the restore image and original image. However, this method has some constrains, if parameter selection improper, it generates ringing effect easily. Usually, most users select parameter by rule of thumb, so they frequently fail to generate the optimal solution. In order to get high quality restore image, eliminate the ringing effect, a new approach based on particle swarm optimization (PSO) Wiener Filter was proposed, which automatically adjusts the parameter for Wiener Filter, this method seek the optimal solution by transferring information between individuals and information sharing, which is a highly efficient parallel search algorithm, insuring the accuracy of parameter selection, effectively reducing the ringing effect after image restoration, improve image quality of restoration.

Abstract: Interferogram noise filter is one of the key technologies which use synthetic aperture radar interferometry phase to extract digital elevation model. However, the interference fringes’ details are often reduced when complex interferogram is filtered, and this leads to inaccurate phase unwrapping result, for this combined filter method based on terrain factors is proposed. Filter method can be selected through weight factor associated with the terrain slope in the filter process, and Wiener filter method is implemented in flat terrain area, frequency estimated filter method is achieved in steep terrain area. Then the new filter method is applied to deal with data where the region of Quebec, Canada. This proves that the new filter algorithm proposed in this paper can effectively suppress noise and better maintain stripe details.

Abstract: The traditional combination filter method in the practical process is often two layers of composite filtering de-noising for the image containing the gaussian mixture noise and pulse noise. This paper proposes a three filter combination algorithm based on the two layers filters, To the Gaussian and pulse mixed noise of the remote sensing image, we use wavelet threshold de-nosing and adaptive median filter de-nosing, and then using the third layer adaptive Wiener filtering de-noising to remove the residual noise. Through theoretical analysis and practical application, the de-nosing results of this method is obvious in processing mixed noise of remote sensing image, this is a practical method of combination filtering de-noising, it can be widely used in the field of image processing.

Abstract: Comparing with the traditional fixed carrier frequency signal, using FH (Frequency-Hopped) signals improved the performance of anti-interference of the TT&C system when bring the low signal tracking accuracy. In order to solve this problem, this paper proposed a loop structure of using wiener filter, the filter coefficient was deduced. Simulation results show that the loop tracking precision was increased after the optimization, and the improvement has relations with the filter order n. When, the speed measuring precision reached 30cm/s which was increased about 3 times than did not use wiener filter.

Abstract: Measured data of hydrophone array could be interfered by underwater noise,so its essential to enhance the performance of suppressing interference for adaptive array processing. How to improve the performance of Double Stages Wiener Filter was discussed based on configuration principles. The influences of interference angle, array unit number and interference-to-noise ratio (INR) to suppressing interference have been analyzed through principle analysis and simulation experiments under different circumstances, including single or multiple disturb signals. Experiments show that the performance of suppressing interference depends on interference angle and INR more and array unit sum a little.

Abstract: Measured data of hydrophone array could be interfered by underwater noise,so its essential to enhance the performance of suppressing interference for adaptive array processing. How to improve the performance of Double Stages Wiener Filter was discussed based on configuration principles. The influences of interference angle, array unit number and interference-to-noise ratio (INR) to suppressing interference have been analyzed through principle analysis and simulation experiments under different circumstances, including single or multiple disturb signals. Experiments show that the performance of suppressing interference depends on interference angle and INR more and array unit sum a little.

Abstract: A framework is proposed to reconstruct a super resolution image from a single low resolution image with Gaussian noise. The degrading processes of Gaussian blur, down-sampling, and Gaussian noise are all considered. For the low resolution image, the Gaussian noise is reduced through Wiener filtering algorithm. For the de-noised low resolution image, iterative back projection algorithm is used to reconstruct a super resolution image. Experiments show that de-noising plays an important part in single-image super resolution reconstruction. In the super reconstructed image, the Gaussian noise is reduced effectively and the peak signal to noise ratio (PSNR) is increased.

Abstract: This paper introduces fuzzy neural network technology into the adaptive filter and makes further research on its structure and algorithms. At first, fuzzy rules are determined and the network structure is built by means of dividing fuzzy subspaces. Secondly, membership functions are chosen layers are defined and the network is trained by adaptive learning algorithm. Thirdly, training error is the minimum with repeating debugging. Finally, linking weight, the central value and width of the network membership function is adjusted by using experience of experts. The optimal performance of Adaptive Wiener Filter is realized based on Fuzzy Neural Networks.

Abstract: We have designed a photoelectric yarn signal acquisition system, which is based on the STM32 processor, having a sample rate up to 270kHz, and uploading data collection through synchronous parallel communication mode; Owing to the large noise of yarn signal and the unobviousness of yarn defect, we respectively adopting wiener filter and mean filter to filter this signal; The simulation result of matlab has manifested that both the wiener filter and mean filter can effectively decrease the noise level of the yarn signal and make the nep defects easier to identify, and that the wiener filter applies to application where the yarn speed is higher , while the mean filter is appropriate to the lower speed spinner.

Abstract: Ship internal equipment vibration will cause the imaging system platform vibration, resulting in blurred images. Wiener Filter is often used to restore the motion blurred image. The principle of the method expects to minimize the mean square error between the restore image and original image. However, this method has some constrains, and it generates ringing effect easily. In order to get high quality restore image, eliminate the ringing effect, a new approach based on an adaptive genetic algorithm (AGA) Wiener Filter was proposed, which automatically adjusts the SNR parameter value for Wiener Filter, this method selects crossover probability and mutation probability according to the fitness values of the object function, therefore reduces the convergence time and improves the precision of simple genetic algorithm (SGA), insuring the accuracy of parameter selection, effectively reducing the ringing effect after image restoration, improve image quality of restoration.