Impulse noise

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

Removal of fixed valued impulse noise by improved Trimmed Mean Median filter

Abstract: Impulse noise removal is considered one of the most burning topic in digital image processing (DIP). When an image is formed, factors like lighting (source, and intensity) and camera characteristics like the sensor response, lenses and also atmospheric condition affect the presence of the image. It hides the important fine points and information of images. In order to enhance the qualities of the image, the removal of noises becomes imperative and that should not be at the cost of any loss of image information like edges. Removal of noise is one of the most important pre-processing tasks of different of image analysis works and tasks like image enhancement, steganography, segmentation and other enhancement related process. In this research article, we have proposed a new method for the removal and restoration of gray images is introduced, when images are corrupted by impulse noise. This method proposed a novel combination of Mean. Median and trimmed value concept for elimination of fixed valued impulse noise. Our methodology ensures a better performance for different level low, medium and high density of fixed value impulse noise as compare to the other famous filters like Standard Median Filter (SMF), Decision Based Median Filter (DBMF) and Modified Decision Based Median Filter (MDBMF) etc. The main objective of the proposed method is to improve not only a peak signal to noise ratio (PSNR) but also improve the visual perception and reduction in blurring of the resultant image. In the proposed method when previous pixels values, 0's and 255's are present in the particular window and all the pixel values are 0's and 255's then the remaining corrupted pixels are substituted by mean and median value. Proposed methodology was tested on gray-scale images like Mandrill and Lena. The experimental result shows improved value of peak signal to noise ratio (PSNR) and mean square error (MSE) values with better visual and human perception.

Coded 64-CAP ADSL in an impulse-noise environment-simulation results

Abstract: This paper describes performance results of E1-ADSL (2.048 Mb/s asymmetrical digital subscriber line) transmission based on carrierless amplitude/phase modulation (CAP) in an impulse-noise environment. Various coding schemes for error protection are investigated. Code options are Reed Solomon code with interleaving, array code and trellis coding, or interleaved trellis coding. The simulation results are based on real measured impulses from an impulse-noise measurement campaign carried out by German Telekom. The inter-arrival times between impulses were either assumed to be constant (worst-case scenario) or were delivered from a distinctive stochastic generator with an inter-arrival time density according to a model also derived in the German campaign. It was found that the RS codes, even with a quite small error-correcting capability, achieved acceptable error performance. Array codes can also be a low-complexity alternative. Trellis coding alone, as expected, was not very effective against the impulse noise.

Power-line communications channel estimation and tracking by a competitive neural network

Abstract: In this paper, a decision-directed method is proposed for channel estimation and equalization in power-line communication (PLC) based on orthogonal frequency-division multiplexing (OFDM). In the DDE (decision-directed estimation) method proposed, the received subcarrier-symbols are presented to a competitive neural network that adaptively finds the clusters of the QAM (quadrature amplitude modulation) constellation. This method does not require a priori know/edge on the powerline then allowing a blind estimation of the channel with tracking capabilities limited by constraints on the phase changes. Simulations on a realistic indoor power-line system show that the proposed method achieves very good channel estimation and equalization performances and that it is robust to impulsive noise and nonlinearities

Incremental M-estimate-based least-mean algorithm over distributed network

Abstract: An incremental least-mean M-estimate algorithm is proposed for distributed network, which minimises a robust M-estimator-based cost function against impulsive noise via the gradient descent method. Moreover, based on the same frame for implementation, an incremental distributed least-mean p-power algorithm is presented for combating impulsive noise. Simulations verify the superiority of the proposed algorithms in the presence of impulsive noise relative to some existing incremental distributed algorithms.

Directional Total Generalized Variation Regularization for Impulse Noise Removal

Abstract: A recently suggested regularization method, which combines directional information with total generalized variation (TGV), has been shown to be successful for restoring Gaussian noise corrupted images We extend the use of this regularizer to impulse noise removal and demonstrate that using this regularizer for directional images is highly advantageous In order to estimate directions in impulse noise corrupted images, which is much more challenging compared to Gaussian noise corrupted images, we introduce a new Fourier transform-based method Numerical experiments show that this method is more robust with respect to noise and also more efficient than other direction estimation methods