Abstract:A cellular neural network (CNN) is a large-scale nonlinear analog circuit suitable for real-time signal and image processing.CNN can be used for high-speed parallel computation and is easy to be translated into a VLSI implementation.This paper presents one new approach for shape from shading (SFS) using paralleled hardware annealing CNN that performs optimization algorithm.Some practical results are presented and briefly discussed,which demonstrates the successful operation of the proposed algorithm.This new approach is very affordable to parallelism and analog VLSI implementation,which allowing the SFS solution to be performed in real-time.
王怀颖;于盛林;冯 强. 基于细胞神经网络的从阴影恢复形状的新方法[J]. 电子学报, 2006, 34(11): 2120-2124.
WANG Huai-ying;YU Sheng-lin;FENG Qiang. A New Approach for Shape form Shading Based on CNN. Chinese Journal of Electronics, 2006, 34(11): 2120-2124.