Adaptive Filter for Color Impulsive Removal Based on the HSI Color Space

A novel adaptive filter that uses the HSI color space for removal impulsive noise in color images is presented in this paper. The proposed method is an adaptive filter according to the information of pixels, only to these pixels detected impulse noise with noise identity matrix. All of processing is based on the HSI color space. The extensive experimental results have shown that the proposed solution can provide the best noise suppression results and better preserve thin lines, edges and image details and yield better image quality compared to other filters. In addition, the proposed method is in line with requirements of the human visual sensitivity.

[1]  Samuel Morillas,et al.  New adaptive vector filter using fuzzy metrics , 2007, J. Electronic Imaging.

[2]  Joachim Weickert,et al.  Scale-Space Properties of Nonstationary Iterative Regularization Methods , 2000, J. Vis. Commun. Image Represent..

[3]  Thierry Blu,et al.  A New SURE Approach to Image Denoising: Interscale Orthonormal Wavelet Thresholding , 2007, IEEE Transactions on Image Processing.

[4]  Brendt Wohlberg,et al.  Efficient Minimization Method for a Generalized Total Variation Functional , 2009, IEEE Transactions on Image Processing.

[5]  Thomas Brox,et al.  Nonlinear structure tensors , 2006, Image Vis. Comput..

[6]  Abdullah Bal Optical supervised filtering technique based on Hopfield neural network , 2004 .

[7]  Konstantinos N. Plataniotis,et al.  Self-adaptive algorithm of impulsive noise reduction in color images , 2002, Pattern Recognit..

[8]  Aleksandra Pizurica,et al.  Estimating the probability of the presence of a signal of interest in multiresolution single- and multiband image denoising , 2006, IEEE Transactions on Image Processing.

[9]  Hong Ren Wu,et al.  A robust structure-adaptive hybrid vector filter for color image restoration , 2005, IEEE Transactions on Image Processing.

[10]  M. Emre Celebi,et al.  Robust switching vector median filter for impulsive noise removal , 2008, J. Electronic Imaging.

[11]  I. Selesnick,et al.  Bivariate shrinkage with local variance estimation , 2002, IEEE Signal Processing Letters.

[12]  Rastislav Lukac,et al.  Selection weighted vector directional filters , 2004, Comput. Vis. Image Underst..