One of the fundamental problems in signal processing is to enhance a signal which has been corrupted by an additive noise. In this thesis, the problem of deviating the effects of camera noise corrupting the dialog of a film soundtrack is examined. Two methods of noise reduction are investigated: adaptive noise cancellation with a synthesized reference signal, and spectral subtraction. It is fou...

In this paper an efficient algorithm is proposed to remove additive white Gaussian noise(AWGN) with edge preservation. A function is used to separate the filtering mask to two sets according to the direction information. Then, we calculate the mean and standard deviation of the pixels in each set. In order to preserve the details, we also compare standard deviations between the two sets to find...

This paper presents a sliding mode filter for removing noise. It effectively removes impulsive noise and high-frequency noise with producing smaller phase lag than linear filters. In addition, it is less prone to overshoot than previous sliding mode filters and it does not produce chattering. It is computationally inexpensive, and thus suitable for realtime applications. The proposed sliding mo...

–Fuzzy filter is a filter technique for the removal of random impulse noise in color video. By working with different successive filtering steps, a very good tradeoff between detail preservation and noise removal is obtained. So, to noise is filtered step by step. In each step, noise pixels in color frame are detected using fuzzy rules, which are very useful for the processing of human knowledg...

A new image denoising algorithm to deal with the Poisson noise model is given, which is based on the idea of Non-Local Mean. By using the ”Oracle” concept, we establish a theorem to show that the Non-Local Means Filter can effectively deal with Poisson noise with some modification. Under the theoretical result, we construct our new algorithm called Non-Local Means Poisson Filter and demonstrate...

A Median filter is used for eliminating Salt & Pepper Impulse noise and Wiener filter is used for eliminating Gaussian noise. This paper presents a hybrid filter for removal of both types of noises. Two Hybrid filters are presented for eliminating Salt and Pepper noise and Gaussian noise simultaneously from a noisy image. The first filter is a combination of a variant of Median filter and Wiene...

Stochastic (on-line) learning can be faster than batch learning. However, at late times, the learning rate must be annealed to remove the noise present in the stochastic weight updates. In this annealing phase, the convergence rate (in mean square) is at best proportional to l/T where T is the number of input presentations. An alternative is to increase the batch size to remove the noise. In th...

This paper examines the applicability of Random Matrix Theory to portfolio management in finance. Starting from a group of normally distributed stochastic processes with given correlations we devise an algorithm for removing noise from the estimator of correlations constructed from measured time series. We then apply this algorithm to historical time series for the Standard and Poor’s 500 index...

Images arising from low-intensity settings such as in X-ray astronomy and computed tomography scan often show a relatively weak but constant background noise across the frame. The background noise can result from various uncontrollable sources. In such a situation, it has been observed that the performance of a denoising algorithm can be improved considerably if an additional thresholding proce...

Denoising images is a classical problem in low-level computer vision. In this paper, we propose an algorithm which can remove iteratively salt and pepper noise based on neighbourhood while preserving details. First, we compute the probability of different window without free noise pixel by noise ratio, and then determine the size of window. After that the corrupted pixel is replaced by the weig...