A biologically inspired neural network for image enhancement
Yinghua Li, Tian Pu, Jian Cheng · 2010
A promising trend of image processing is to incorporate some knowledge on human visual system. In this paper, we propose an improved pulse coupled neural network (PCNN) for image enhancement. We apply the passive membrane equation, which is known as a model for describing the ON-OFF opponent property of the receptive fields of the retinal ganglion cells, as the linking field to modulate feeding field input of the PCNN and obtain the enhanced neural pulse as the output image. Initially, the RGB image is converted to luminance and chrominance images. Only the achromatic image is enhanced. Finally the RGB image is reconstructed from the enhanced luminance component along with the original chrominance component. The experimental results show the effectiveness of the method.