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Human Visual Characteristics Inspired Adaptive Image Quantization Method.

Authors :
Huang, Yi
Ma, Jianlin
Du, Songlin
Ma, Yide
Source :
Sampling Theory in Signal & Image Processing. 2014, Vol. 13 Issue 2, p111-124. 14p.
Publication Year :
2014

Abstract

Combined with human visual characteristics, this paper proposes an adaptive image quantization method using pulse coupled neural networks (PCNN). It is acknowledged that PCNN satisfies human visual characteristics which can be used to quantize images. We have been trying to obtain the optimal image quantized with minimum amount of data for a long time and finally discover that the proposed algorithm comes up to the expected standard. First, the gray scale image is imported into PCNN and then the parameters of PCNN are set automatically. Secondly, the image is quantized by the hand of proposed algorithm. The experimental results of the gray natural images from the standard image library prove the validity and efficiency of our proposed quantization method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15306429
Volume :
13
Issue :
2
Database :
Academic Search Index
Journal :
Sampling Theory in Signal & Image Processing
Publication Type :
Academic Journal
Accession number :
151923887
Full Text :
https://doi.org/10.1007/BF03549575