Blur Classification Using Wavelet Transform and Feed Forward Neural Network

Blur Classification Using Wavelet Transform and Feed Forward Neural Network

Автор: Shamik Tiwari, V. P. Shukla, S. R. Biradar, A. K. Singh

Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs

Статья в выпуске: 4 vol.6, 2014 года.

Бесплатный доступ

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.

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Blur, Motion, Defocus, Wavelet Transform, Neural Network

Короткий адрес: https://sciup.org/15014643

IDR: 15014643

Список литературы Blur Classification Using Wavelet Transform and Feed Forward Neural Network

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