Papers by Keyword: Wiener Filtering

Abstract: In the paper, degradation and restoration model is introduced. Image restoration method using inverse filtering and using wiener filtering are studied and implemented. A new method of image restoration is proposed by combining histogram equalization and median filtering. Comparing three methods by MATLAB simulation, the results show that the new method can effectively restore degradation image with comparatively high restoration efficiency.

Abstract: Aiming at traditional methods cannot get good performance in noisy environments, an improved method for pitch detection was proposed. In this method, noisy speech was enhanced by using wiener filtering at first, and then analyzing linear prediction residual and power spectrum reprocessing, the feature of weighted residual power spectrum reprocessing was extracted to detect speech pitch period. Experimental results indicate that the proposed pitch detection method has higher reliability with lower computational complexity. It can detect pitch more accurately in low SNR environments and has better robustness.

Abstract: eech enhancement based on Wiener filtering has good noise robustness, and it is efficient and easy-to-implement. In this paper, Wiener filtering and its modified form, Iterative Wiener Filtering are demonstrated. Then, their respective advantages and disadvantages are outlined. Finally, the application field and location of each method are also pointed out.

Abstract: With characteristics of impulse noise and Gaussian noise, we propose a new denoising method to infrared image. We use Sobel operator to obtain boundary information, and determine the denoising method based on the pixel number of the peer group, denoising impulse noise and Gaussian noise with median filter and Wiener filtering. Experimental results are provided to show that the proposed filter achieves a promising performance in PSNR and boundary information, compared with the median filtering, Wiener filtering and peer group algorithms.

Abstract: Image restoration is an important application of the digital image processing. Unlike traditional restoration algorithms that operate on a blurred image to recover the original, we propose a technique that the correction should be applied to the original image before blurring. To accomplish this, we approximate the Point-Spread-Function (PSF) of different defocus blur images by the circular disk. According to the estimated PSF, the original image is pro-processed based on Wiener filtering and High Dynamic Range (HDR) compression. Experiments results show that using this technique can help ameliorate the visual blur and the defocus images finally have a sharp vision.

Abstract: We propose a new design to detect a target degraded by non-uniform illumination function and additive noise placed in non-overlapping background noise. The method is based on estimated illumination function and Wiener filtering theory, which provides robustness to non-uniform illumination and noisy conditions, especially for non-overlapping background noise. Computer simulation results are presented to verify the performance of the method.

Abstract: A blind image restoration method is proposed to improve the quality of the image blurred by camera defocus and system noise. Firstly, the focus point spread function (PSF) of the blurred image is estimated through error-parameter analysis method. Secondly, the Signal-to-Noise Ratio (SNR) of the blurred image is estimated through local deviation method. Thirdly, utilizing the estimated defocus PSF and SNR, image restoration is performed through Wiener filtering method, in which circulation boundary method is adopted to reduce ringing effect. Experimental results show that the SNR of the blurred image is estimated approximately, and verify the great effect of SNR estimation in blind image restoration.

Abstract: To the deficiencies of traditional methods for avoiding motion image blurring, a motion blur image restoration method is studied based on Wiener filtering in this paper. The formation factors of motion-blurred images and the imaging process are analyzed, and the motion blur degradation model is established. It introduced the working principle of Wiener filtering, described the steps of blurred image restoration in details. The experiment testing and data analyzing are also conducted. Experimental results showed that the method can has good performance.

Abstract: Error correction of optical complex surfaces in computer-controlled optical surfacing (CCOS) is primary important. This paper discusses some methods, i.e. Fourier transform method, Wiener filtering method, directive method and iterative method, for calculating dwell time or relative pressure in the CCOS for error-correcting, which are enlightened from the digital image processing techniques. However, these error correction methods are different from the image processing because they are not a subject of solving the causal signal but a problem of an iterative process. The simulation results show that the Wiener filtering method is good and reliable when the correlative parameters in the fabrication are kept consistent.