Blur parameters identification for simultaneous defocus and motion blur

Abstract

Motion blur and defocus blur are common cause of image degradation. Blind restoration of such images demands identification of the accurate point spread function for these blurs. The identification of joint blur parameters in barcode images is considered in this paper using logarithmic power spectrum analysis. First, Radon transform is utilized to identify motion blur angle. Then we estimate the motion blur length and defocus blur radius of the joint blurred image with generalized regression neural network (GRNN). The input of GRNN is the sum of the amplitudes of the normalized logarithmic power spectrum along vertical direction and concentric circles for motion and defocus blurs respectively. This scheme is tested on multiple barcode images with varying parameters of joint blur. We have also analyzed the effect of joint blur when one blur has same, greater or lesser extents to another one. The results of simulation experiments show the high precision of proposed method and reveals that dominance of one blur on another does not affect too much on the applied parameter estimation approach.

Blind identification of linear degradation operators in the Fourier domain

“…[14] A generalized regression neural network is a dynamic neural network architecture that was utilized for identification of motion blur and defocus parameters. [16] Results have showed that proposed scheme for blur parameter identification is equally accurate with each network model. Actually, composite degradations can be considered as a combination of the basic distortion operators.…”

Motion Blur Invariant for Estimating Motion Parameters of Medical Ultrasound Images

“…Based on the main principles of the image blur, PSF could be estimated in terms of two parameters of the motion blur: the angle and the length of motion, whose values are often non-existent by reason of the intrinsic nature of ultrasound motions and speckle. There are various solutions for blur parameters estimation but the well-known method is the blind image deblurring algorithms that evaluates the estimated parameters of the PSF as motion angle/length to obtain a sharp reconstructed version of degraded image 28,29 .…”

Efficient Image Retrieval through Hybrid Feature Set and Neural Network

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