Title :
BM3D Frames and Variational Image Deblurring
Author :
Danielyan, Aram ; Katkovnik, Vladimir ; Egiazarian, Karen
Author_Institution :
Dept. of Signal Process., Tampere Univ. of Technol., Tampere, Finland
fDate :
4/1/2012 12:00:00 AM
Abstract :
A family of the block matching 3-D (BM3D) algorithms for various imaging problems has been recently proposed within the framework of nonlocal patchwise image modeling , . In this paper, we construct analysis and synthesis frames, formalizing BM3D image modeling, and use these frames to develop novel iterative deblurring algorithms. We consider two different formulations of the deblurring problem, i.e., one given by the minimization of the single-objective function and another based on the generalized Nash equilibrium (GNE) balance of two objective functions. The latter results in the algorithm where deblurring and denoising operations are decoupled. The convergence of the developed algorithms is proved. Simulation experiments show that the decoupled algorithm derived from the GNE formulation demonstrates the best numerical and visual results and shows superiority with respect to the state of the art in the field, confirming a valuable potential of BM3D-frames as an advanced image modeling tool.
Keywords :
game theory; image denoising; image restoration; stereo image processing; variational techniques; BM3D frame; BM3D image modeling; block matching 3D algorithm; deblurring problem; decoupled algorithm; denoising operation; generalized Nash equilibrium; iterative deblurring algorithm; single objective function; variational image deblurring; Adaptation models; Algorithm design and analysis; Image reconstruction; Image restoration; Mathematical model; Signal processing algorithms; Transforms; Deblurring; frames; image modeling; image reconstruction; sparse representations; Algorithms; Artifacts; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Models, Statistical; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2011.2176954