共查询到10条相似文献,搜索用时 62 毫秒
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在图像复原算法中,单纯的空间域或者频域滤波算法简单易实现,但需要较多图像退化的先验知识。基于贝叶斯理论的迭代复原算法复原效果好,但耗时长。针对这一矛盾,利用小波变换的多分辨特性,对不同的小波系数特性采用不同的算法进行恢复,提出了一种基于小波域维纳滤波的图像复原算法。实验结果证明,所提方法在保证图像复原质量的同时相对提高了复原算法的效率,是一种有效的方法。 相似文献
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M. El. Badaoui J. Danire F. Guillet C. Servire 《Mechanical Systems and Signal Processing》2005,19(6):1209-1217
The main purpose of this study is to characterize the relative noise given out by a diesel engine, around the Top Dead Centre (TDC) by quantifying the proportions of “mechanical noise” originating mainly from piston-slap on the one hand and ‘thermal noise” originating from combustion on the other hand. Two different approaches are described here to solve this problem.In the first part of the paper, the cylinder pressure is measured and used as a reference in order to reconstruct the thermal noise. Next, we propose a method based on applying a cyclic Wiener filter to the measured cylinder pressure in order to separate the noises of mechanical and thermal origins. The final result is to reduce the engine resulting noise.The second part of the paper is devoted to blind source separation (BSS) methods applied on signals issued from accelerometers placed on one of the cylinders. It develops a BSS method based on a convolutive model of non-stationary mixtures and introduces a new method based on the joint diagonalization of time varying spectral matrices of the observations. Both methods are then applied to real data and the estimated sources are finally validated by several physical arguments. 相似文献
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小波图像去噪已经成为目前图像去噪的主要方法之一。该文尝试把小波变换与自适应中值滤波这两种去噪方法相结合,对同时含有高斯噪声和椒盐噪声的图像进行了去噪研究。实验结果表明,此方法在去除噪声的同时也较好地保留了原始图像的边缘信息,效果不仅优于单一的小波变换或普通中值滤波的方法,更优于将小波变换与普通中值滤波相结合的方法。 相似文献
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V. G. Galalu V. V. Sarychev M. M. Klopot 《Optoelectronics, Instrumentation and Data Processing》2009,45(3):272-276
This paper presents the results of modeling of several digital filtering algorithms of the ADC output codes for suppressing periodic and impulse noise signals and normal noise. The algorithms were tested in LabVIEW. It was shown that they provided real-time suppression of normal and impulse noise to a level from ?57 to ?63 dB. 相似文献
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During the last three decades, several techniques have been proposed for signal-to-noise ratio (SNR) and noise variance estimation in images, with different degrees of success. Recently, a novel technique based on the statistical autoregressive model (AR) was developed and proposed as a solution to SNR estimation in scanning electron microscope (SEM) image. In this paper, the efficiency of the developed technique with different imaging systems is proven and presented as an optimum solution to image noise variance and SNR estimation problems. Simulation results are carried out with images like Lena, remote sensing, and SEM. The two image parameters, SNR and noise variance, are estimated using different techniques and are compared with the AR-based estimator. 相似文献
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A new technique based on cubic spline interpolation with Savitzky–Golay noise reduction filtering is designed to estimate signal‐to‐noise ratio of scanning electron microscopy (SEM) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first‐order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real‐time SEM images, without generating corruption or increasing scanning time. 相似文献
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Image processing is introduced to remove or reduce the noise and unwanted signal that deteriorate the quality of an image. Here, a single level two‐dimensional wavelet transform is applied to the image in order to obtain the wavelet transform sub‐band signal of an image. An estimation technique to predict the noise variance in an image is proposed, which is then fed into a Wiener filter to filter away the noise from the sub‐band of the image. The proposed filter is called adaptive tuning piecewise cubic Hermite interpolation with Wiener filter in the wavelet domain. The performance of this filter is compared with four existing filters: median filter, Gaussian smoothing filter, two level wavelet transform with Wiener filter and adaptive noise Wiener filter. Based on the results, the adaptive tuning piecewise cubic Hermite interpolation with Wiener filter in wavelet domain has better performance than the other four methods. 相似文献