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Defocus Blur Parameter Estimation in Barcode Images using Fast Discrete Curvelet Transform

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


The aim of image restoration techniques is to recover the original image from a degraded observation. One of the most common degradation phenomena in images is defocus blur. In case of blind image restoration accurate estimation of defocus blur parameters is required for deblurring of defocused images. This paper proposes a novel technique for estimating the parameter of defocus blur. It uses Curvelet transform to find the features of the blurred images and a radial biases neural network to estimate the blur parameter. This work is tested on different barcode images with varying degrees of defocus blur. The simulation results of proposed method are found more accurate than the existing methods.


Image Restoration; Defocus Blur; Curvelet Transform; Radial Biases Neural network.

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