International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 6, No. 4, 8 Apr. 2014
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Blur Classification Using Wavelet Transform and Feed Forward Neural Network
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Author(s)
Shamik Tiwari
1,*
V. P. Shukla
1
S. R. Biradar
2
A. K. Singh
1
Index Terms
Blur, Motion, Defocus, Wavelet Transform, Neural Network
Abstract
Image restoration deals with recovery of a sharp image from a blurred version. This approach can be defined as blind or non-blind based on the availability of blur parameters for deconvolution. In case of blind restoration of image, blur classification is extremely desirable before application of any blur parameters identification scheme. A novel approach for blur classification is presented in the paper. This work utilizes the appearance of blur patterns in frequency domain. These features are extracted in wavelet domain and a feed forward neural network is designed with these features. The simulation results illustrate the high efficiency of our algorithm.
Cite This Paper
Shamik Tiwari, V. P. Shukla, S. R. Biradar, A. K. Singh, "Blur Classification Using Wavelet Transform and Feed Forward Neural Network", International Journal of Modern Education and Computer Science (IJMECS), vol.6, no.4, pp.16-23, 2014. DOI:10.5815/ijmecs.2014.04.03
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