Blur identification is one important part of image restoration
process. Linear motion blur is one of the most common degradation
functions that corrupts images. Since 1976, many researchers tried to
estimate motion blur parameters and this problem is solved in noise free
images but in noisy images improvement can be done when image SNR
is low. In this paper we have proposed a method to estimate motion
blur parameters such as direction and length using Radon transform
and Feed-Forward back propagation neural network for noisy images. To
design the desired neural network, we used Weierstrass approximation
theorem and Steifel reference Sets. The experimental results showed algorithm
precision when SNR is low and they were very satisfactory.
کلید واژگان :
Linear Motion blur, Restoration, Neural network, noisy images.
