A mixed noise image filtering method using weighted-linking PCNNs

Image is often degraded by more than one type of noise. In order to design an efficient filter to remove mixed noise from image, this paper proposes a weighted-linking pulse coupled neural network (PCNN) model so as to construct a two-channel parallel noise filter using four PCNNs of this model. This filter detects noise using the pulses generated by neurons, and iteratively removes noise by the pixel signal variation of pulse neurons. The filtering parameters and the iteration stopping conditions are discussed. Experiments show that the proposed PCNN-based filtering method is fast and effective for removing single impulse noise, additional Gaussian noise, as well as the mixed noise of them.

[1]  Yrjö Neuvo,et al.  Detail-preserving median based filters in image processing , 1994, Pattern Recognit. Lett..

[2]  Erkan Beşdok,et al.  A new method for impulsive noise suppression from highly distorted images by using Anfis , 2004, Eng. Appl. Artif. Intell..

[3]  Heggere S. Ranganath,et al.  Perfect image segmentation using pulse coupled neural networks , 1999, IEEE Trans. Neural Networks.

[4]  Rolf Unbehauen,et al.  An adaptive recursive 2-D filter for removal of Gaussian noise in images , 1992, IEEE Trans. Image Process..

[5]  Yehoshua Y. Zeevi,et al.  Forward-and-backward diffusion processes for adaptive image enhancement and denoising , 2002, IEEE Trans. Image Process..

[6]  K. E. Tait,et al.  Image recovery using the anisotropic diffusion equation , 1996, IEEE Trans. Image Process..

[7]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Gérard Thomas,et al.  A deconvolution technique using optimal Wiener filtering and regularization , 1999, Signal Process..

[9]  Jeffery Johnson,et al.  Pulse coupled neural networks for image processing , 1995, Proceedings IEEE Southeastcon '95. Visualize the Future.

[10]  Wenbin Luo,et al.  An efficient detail-preserving approach for removing impulse noise in images , 2006, IEEE Signal Processing Letters.

[11]  F. Russo Technique for image denoising based on adaptive piecewise linear filters and automatic parameter tuning , 2006, IEEE Transactions on Instrumentation and Measurement.

[12]  Heggere S. Ranganath,et al.  Object detection using pulse coupled neural networks , 1999, IEEE Trans. Neural Networks.

[13]  Ling Guan,et al.  A neural network adaptive filter for the removal of impulse noise in digital images , 1996, Neural Networks.

[14]  Tuan D. Pham,et al.  An image restoration by fusion , 2001, Pattern Recognit..

[15]  Md. Kamrul Hasan,et al.  Wavelet-domain iterative center weighted median filter for image denoising , 2003, Signal Process..

[16]  Raul Cristian Muresan,et al.  Pattern recognition using pulse-coupled neural networks and discrete Fourier transforms , 2003, Neurocomputing.

[17]  Martin J. Wainwright,et al.  Image denoising using scale mixtures of Gaussians in the wavelet domain , 2003, IEEE Trans. Image Process..

[18]  Jason M. Kinser,et al.  The intersecting cortical model in image processing , 2004 .

[19]  Rastislav Lukac,et al.  Adaptive vector median filtering , 2003, Pattern Recognit. Lett..

[20]  Jason M. Kinser,et al.  Inherent features of wavelets and pulse coupled networks , 1999, IEEE Trans. Neural Networks.

[21]  Zhang Yi,et al.  A class of binary images thinning using two PCNNs , 2007, Neurocomputing.

[22]  Xiaodong Gu,et al.  Image shadow removal using pulse coupled neural network , 2005, IEEE Transactions on Neural Networks.

[23]  Kannan Ramchandran,et al.  Low-complexity image denoising based on statistical modeling of wavelet coefficients , 1999, IEEE Signal Processing Letters.

[24]  Jason M. Kinser,et al.  Image Processing using Pulse-Coupled Neural Networks , 1998, Perspectives in Neural Computing.

[25]  Bart M. ter Haar Romeny,et al.  Geometry-Driven Diffusion in Computer Vision , 1994, Computational Imaging and Vision.

[26]  Reinhard Eckhorn,et al.  Feature Linking via Synchronization among Distributed Assemblies: Simulations of Results from Cat Visual Cortex , 1990, Neural Computation.

[27]  Naif Alajlan,et al.  Detail preserving impulsive noise removal , 2004, Signal Process. Image Commun..

[28]  S. Mallat A wavelet tour of signal processing , 1998 .

[29]  Michael L. Lightstone,et al.  A new efficient approach for the removal of impulse noise from highly corrupted images , 1996, IEEE Trans. Image Process..

[30]  Lori E. Lucke,et al.  Multi-level adaptive fuzzy filter for mixed noise removal , 1995, Proceedings of ISCAS'95 - International Symposium on Circuits and Systems.

[31]  Fabrizio Russo A method for estimation and filtering of Gaussian noise in images , 2003, IEEE Trans. Instrum. Meas..

[32]  EckhornR.,et al.  Feature linking via synchronization among distributed assemblies , 1990 .

[33]  Charles K. Chui,et al.  A universal noise removal algorithm with an impulse detector , 2005, IEEE Transactions on Image Processing.

[34]  John L. Johnson,et al.  PCNN models and applications , 1999, IEEE Trans. Neural Networks.

[35]  Mostafa Kaveh,et al.  Fourth-order partial differential equations for noise removal , 2000, IEEE Trans. Image Process..

[36]  Ma Yi-de,et al.  Gaussian noise filter based on PCNN , 2003, International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003.

[37]  Kai-Kuang Ma,et al.  A switching median filter with boundary discriminative noise detection for extremely corrupted images , 2006, IEEE Trans. Image Process..

[38]  Junying Zhang,et al.  An adaptive method for image filtering with pulse-coupled neural networks , 2005, IEEE International Conference on Image Processing 2005.