31results about How to "Impulse noise suppression" patented technology

The invention provides a noise removing circuit having an improved pulse noise detection accuracy irrespective of the intensity of the electric field by selecting a noise detection signal according to the intensity of the electric field. A noise removing circuit comprising a predicting section for predicting the value of an intermediate frequency signal at a predetermined time on the basis of the intermediate frequency signal previously generated before the predetermined time, a detecting section for comparing the difference in magnitude between the predicted value of the intermediate frequency signal at the predetermined time and the value of the previously generated intermediate frequency signal with a predetermined threshold and thereby outputting a second detection signal representing the occurrence of the pulse noise, and a noise removal control unit for selectively outputting to a noise removing unit either a first detection signal representing the occurrence of pulse noise generated by level-detecting the intermediate frequency signal of the received signal or the second detection signal as a signal for interpolating the period when the pulse noise occurs according to the electric field intensity signal generated from the intermediate frequency signal.

A system and method provide for an adaptive median filter with edge protection and four line buffers to remove the impulse noise for a Bayer pattern image. The system and method separates the Bayer pattern image data into different channels by color and applies the adaptive median filter to remove the impulse noise on each channel. The adaptive median filter has five threshold values that may be modified to achieve different light condition response based on the detected noise level of the image. Thus, proper threshold values with better brightness response to the input pixels may be applied and impulse noise may be suppressed effectively, while preserving image details.

The invention provides a noise suppression method applied to a broadband OFDM power line communication system. According to the noise suppression method, discrete Fourier transform is carried out on an OFDM signal at a receiving terminal; a protection frequency band signal is extracted from an output result and that is, a useless part distributed between two adjacent channels in the frequency spectrum is extracted; a correlated parameter of a pulse noise is estimated by combining time-domain and frequency-domain methods; and according to the estimated parameter of the pulse noise, a proper envelope window function is constructed to suppress the pulse noise in the time domain. Therefore, the pulse noise can be suppressed effectively; the frequency spectrum leakage can be reduced substantially; and performances of the broadband power line communication system can be improved.

The invention discloses a salt and pepper noise filtering method based on a color image, relating to the image processing field. In the method, based on a vector median filter for detecting a gradual switch median, a vector median filtering method is utilized to effectively inhibit the pulse noise, and the advantages of the gradual switch median detection method are combined to effectively eliminate the noise and synchronously avoid blurring of the image details; the gradual way is firstly reflected in that the detecting process of each iteration is performed based on the result of previous detection; with respect to a color image with high contaminating rate, densely distributed noise can be gradually detected one by one through the iteration process and is avoided being remained by regarding the noise as the real information of the image; the iteration process prevents the small noise which are densely distributed originally from gathering to be a large noise area; and the filteringprocess is used for filtering the noise based on the previous detecting results.

This invention provides an impulsive noise suppression method in orthogonal frequency division multiplexing. The method comprises an equalization and de-mapping step for estimating a preliminary estimation of signal and a total noise estimation by utilizing ideal channel estimation, de-mapping, and pilot insertion technique on received signal; and a SNR comparison step for determining a SNR by dividing said preliminary estimation of signal and said total noise estimation and comparing said SNR with a threshold value.

The invention belongs to the technical field of non-stationary signal modulation and analysis, and discloses an LFM signal modulation parameter estimation method under alpha stable distribution noise.The method comprises the following steps of carrying out generalized extension linear chirplet transform on a received LFM signal to obtain a time-frequency analysis image; carrying out Radon transform on the time-frequency analysis image, calculating a maximum value of the time-frequency analysis image, and estimating an angle estimation frequency modulation slope corresponding to the maximum value; and constructing a demodulation reference signal by utilizing the frequency modulation slope, multiplying the demodulation reference signal by an original signal to obtain a demodulation signal,carrying out generalized Fourier transform on the demodulation signal, and estimating an initial frequency by utilizing the position of the maximum value. When a generalized signal-to-noise ratio is larger than 0dB, a normalized mean square error of the frequency modulation slope estimation of the LFM signal is smaller than -33dB; and when the generalized signal-to-noise ratio is larger than -6dB,the normalized mean square error of the initial frequency estimation of the LFM signal is less than or equal to -22.4dB.

A method for suppressing impulse noises is provided. The method is employed to receive a sample stream x[n], and to detect and suppress the interruption of impulse noise to the samples, wherein the sample stream x[n] includes a plurality of samples and n represents a discrete-time independent variable. The method includes comparing the energy sum of a (k−1)th sample and a kth sample multiplied by a first constant with a first threshold, comparing energy sum of the kth sample and a (k+1)th sample multiplied by a second constant with a second threshold while the energy sum of the (k−1)th sample and the kth sample multiplied by the first constant is greater than the first threshold, and replacing the kth sample with a first replacement sample to output while the energy sum of the kth sample and the (k+1)th sample multiplied by the second constant is greater than the second threshold.

The invention provides impulse noise suppression and demapping soft decision method and system in a multi-carrier system, wherein the method comprises the following steps of: carrying out statistics on power of receiving signals by an A / D (Analog to Digital) module by a power statistical module, comparing the power with a set threshold, judging whether impulse noise exists in the received signals or not, and if the impulse noise exists, generating an impulse indication signal and a confidence indication signal by the power statistical module; carrying out impulse noise suppression processing on the received signals which are judged to have the impulse noise by an AGC (Automatic Gain Control) module and carrying out power regulation on the receiving signal according to the impulse indication signal; feeding back the power-regulated receiving signal to the A / D module; setting up a confidence weight number according to the confidence indication signal by a demapping module, and carrying out soft decision processing on received information output from the A / D module according to the confidence weight number. The invention can effectively suppress the impulse noise and provides different confidence indications according to different impulse noise types to ensure the reliability of the demapping soft decision.

The invention discloses a method for super-resolution time delay estimation of a narrowband multipath signal in an impulse noise environment, and belongs to the technical field of signal processing. It is characterized in that the exponential Gaussian kernel function is used to suppress impulse noise to obtain a higher accuracy rate of time delay estimation; the multipath signal model is converted by using Fourier transform and inverse Fourier transform to obtain a false signal suitable for the MUSIC algorithm model to achieve super-resolution time delay estimation. Experiments prove that the present invention can obtain a higher correct rate of time delay estimation under the condition of strong impulsive noise.

The invention discloses a method for suppressing image impulse noise based on an iterative non-local mean value, which is mainly used to solve the problems that the existing method cannot preserve image detail information in the denoising process and cannot restore a clear image under high noise density. The implementation steps are: (1) use the histogram method to detect the noise position on the noise image; (2) pre-filter the noise image by selecting and switching the median filter; (3) use iterative non-local filtering on the pre-filtered image The average method is used to obtain a clear image that effectively suppresses impulse noise. Simulation experiments show that the present invention is superior to existing algorithms in subjective visual effects and objective evaluation results under the condition of different degrees of impulse noise, and can be used to suppress high-density impulse noise and restore clear images.

A liquid crystal display drive circuit that suppresses a pulse noise in a liquid crystal display panel without increasing a mounting area is offered. A common signal COMi is varied in a staircase waveform with an increment of 1 / 3 VLCD in such a way that a high electric potential VLCD->a first intermediate electric potential VLCD1->a second intermediate electric potential VLCD2->a low electric potential VSS, when the common signal COMi varies by the maximum amplitude, in other words, when the common signal COMi makes a transition from the high electric potential VLCD to the low electric potential VSS. The segment signal SEGj is varied similarly in a staircase waveform in such a way that the low electric potential VSS->the second intermediate electric potential VLCD2->the first intermediate electric potential VLCD1->the high electric potential VLCD when the segment signal SEGj makes a transition from the low electric potential VSS to the high electric potential VLCD. A peak value of the pulse noise due to a capacitive coupling can be reduced to 1 / 3 of that in the prior art.

The invention discloses a pulse noise suppression method for sparse iterative covariance estimation in power lines. At the sending end, the discrete time-domain signal with a cyclic prefix is ​​transmitted to the receiving end through a channel; at the receiving end, the received signal is first projected On the empty subcarrier matrix, a mixed signal containing only impulse noise and Gaussian noise is obtained; using sparse iterative covariance estimation, the power of the mixed signal is obtained, and then the power of the impulse noise is obtained; the estimated value of the impulse noise is obtained by using the linear mean square error ; Subtract the estimated value of impulse noise from the received signal to complete the suppression of impulse noise; the advantage is that the sparse iterative covariance estimation adopted has a higher resolution, and can estimate the power of the mixed signal more accurately, so that The estimated impulse noise is more accurate, so that the suppression effect of impulse noise is better.

A noise suppression apparatus disclosed is capable of suppressing pulse noise in an input signal even in a situation in which the level of the input signal changes. The pulse noise mixed in the input signal is suppressed, and linear prediction coefficients for the input signal is derived by linear prediction analysis. A prediction residual signal is then calculated from the input signal using the linear prediction coefficient. A threshold value is calculated based on the signal level of the input signal and the signal level of the prediction residual signal is compared with the threshold value. A limit control is performed on the prediction residual signal depending on a result of the comparison, and an output signal is generated based on the prediction residual signal having been subjected to the limit control using the linear prediction coefficient.