DocumentCode
2390036
Title
A biologically inspired neural network for image enhancement
Author
Li, Yinghua ; Pu, Tian ; Cheng, Jian
Author_Institution
Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear
2010
fDate
6-8 Dec. 2010
Firstpage
1
Lastpage
4
Abstract
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.
Keywords
image colour analysis; image enhancement; neural nets; PCNN; biologically inspired neural network; chrominance images; human visual system; image enhancement; image processing; luminance images; pulse coupled neural network; Artificial neural networks; Educational institutions; Humans; Image enhancement; Joining processes; OFDM; Visualization; image enhancement; opponent neural network; pulse coupled neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Signal Processing and Communication Systems (ISPACS), 2010 International Symposium on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-7369-4
Type
conf
DOI
10.1109/ISPACS.2010.5704686
Filename
5704686
Link To Document