A new color image restoration algorithm based on LAB and RBF neural network
Liwei Zhang, Yaping Zhang · 2012
A new color image restoration algorithm is put forward based on LAB and RBF neural network. Firstly, gray image is obtained by the LAB transform method in color image. Image restoration model is got by the operating of the window roaming and training of RBF neural network and the establishment of corresponding relation between motion blurred image and clear image, which is concentrated on the motion blurred image. Finally, the prepared image is recovered according to the model. The motion blurred image can be recovered well with the new algorithm, and color image is got by the clear image according to LAB, which can keep the color information. The recovery effect is more advantaged than the classical algorithms such as Wiener filtering and with small computation.