Impulse noise

About: Impulse noise is a research topic. Over the lifetime, 4816 publications have been published within this topic receiving 63970 citations.

Impulsive noise estimation and cancellation in DSL using compressive sampling

Abstract: Impulsive noise is the bottleneck that determines the maximum length of the DSL. Impulsive noise seldom occurs in DSL but when it occurs, it is very destructive and results in dropping the affected DSL symbols at the receiver as they cannot be recovered. By considering impulsive noise a sparse vector, recently developed sparse reconstruction algorithms can be utilized to combat it. We propose an algorithm that utilizes the null carriers for the impulsive noise estimation and cancellation. Specifically, we use compressive sampling for a coarse estimate of the impulse position, an a priori information based MAP metric for its refinement, followed by MMSE estimation for estimating the impulse amplitudes. We also present a comparison of the achievable rate in DSL using our algorithm and recently developed algorithms for sparse signal reconstruction.

A simple generalized neuro-fuzzy operator for efficient removal of impulse noise from highly corrupted digital images

Abstract: A generalized neuro-fuzzy (NF) operator for removing impulse noise from highly corrupted digital images is presented. The fundamental building block of the operator is a simple 3-input 1-output NF filter. The operator is constructed by combining a desired number of NF filters with a postprocessor. Each NF filter in the structure evaluates a different pixel neighborhood relation. Hence, the number of NF filters in the structure can be varied to obtain the desired filtering performance. Internal parameters of the NF filters are adaptively optimized by training by using a simple artificial training image that can easily be generated in a computer. Simulation results indicate that the proposed operator outperforms popular conventional as well as state-of-the-art impulse noise removal operators and offers superior performance in removing impulse noise from highly corrupted images while efficiently preserving image details and texture.

Signal-dependent rank-ordered-mean (SD-ROM) filter

Abstract: Publisher Summary This chapter presents the signal-dependent rank-ordered-mean (SD-ROM) method for the removal of impulse noise from image data, in which the filtering operation is conditioned on the rank-ordered differences, defined as the differences between the input pixel and the remaining rank-ordered pixels in a sliding window. The chapter discusses two algorithms—one based on a simple detection-estimation strategy involving thresholds, and the other incorporating fuzzy rules. The strategies for the design of the weighting coefficients are presented in the algorithm incorporating fuzzy rules, for recursive and non-recursive implementation, including a least-squares derivation for the non-recursive case, which leads to a close form expression for the optimal weighting coefficients. This chapter also presents computer simulation examples to illustrate the effectiveness of the SD-ROM method using several distinct noise types, including impulsive, Gaussian, and mixed impulsive and Gaussian. Finally, it presents a simple algorithm for restoration of images corrupted by streaks, based on the SD-ROM approach.

A Harmonic Suppression Method Based on Fractional Lower Order Statistics for Power System

Abstract: Impulse noise in power systems would seriously degrade the harmonic suppression performance. To remedy this problem, a novel harmonic suppression method based on fractional lower order statistics (FLOS) is proposed in this paper. In the proposed method, impulse noise is modeled by alpha-stable distribution. Then, the ESPRIT spectrum estimation algorithm is improved by FLOS for impulse noise and used to estimate the fundamental frequency of power signal, and the frequency of each harmonic component is obtained from this estimated frequency. Next, the amplitude of each harmonic component is estimated by a modified recursive least squares (RLS) algorithm. Finally, a harmonic compensation signal is generated by the active power filter based on the estimated frequencies and amplitudes to cancel original harmonics. The proposed method has a competitive advantage that it can suppress harmonics well even if the impulse noise activating and has a fast tracking ability for changing harmonics. Also, due to the use of self-sensing actuator principle, the proposed method can not only guarantee the performance of suppressing harmonics at normal operation states, but also ensure not to amplify harmonics in case of malfunction. The simulation results show that the proposed method has a better harmonic suppression performance than the existing ones under the impulse noise environment. The real experiments are also presented to verify the feasibility of the proposed method.