A novel edge-parameter analysis approach of blur identification for image de-blurring application

In this paper, a novel edge-parameter analysis method of the blu' identification based on the single-threshold Pulse Coupled Neural Networks (PCNN) model is proposed for image de-blurring application. It suits to the identification of the horizontal linear motion blur. This new identification method not only improves on the traditional PCNN, but also uses the normalized local entropy. On the one hand, the new method uses the local entropy which is normalized between 0 and 255. On the other hand, a new model called the single-threshold PCNN is proposed in this article. Comparing with the traditional PCNN, the improved one calculates faster, and it is more sensitive to the image edges. The experimental results which are obtained from the different images and the same image with the different resolution show that the new algorithm is very effective and the curve is the very steady graph. The identification precision is about 4 to 30 pixels.