Image Enhancement Based on Pulse Coupled Neural Network in the Nonsubsample Shearlet Transform Domain
Joint Authors
Song, Yafei
Xing, Yaqiong
Qu, Zhi
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-21
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In this study, pulse coupled neural network (PCNN) was modified and applied to the enhancement of blur images.
In the transform domain of nonsubsample shearlet transform (NSST), PCNN was used to enhance the details of images in the low- and high-frequency subbands, and then the enhanced low- and high-frequency coefficients were used for NSST inverse transformation to obtain the enhanced images.
The results showed that the proposed method can produce higher-quality images and suppress noise better than traditional image enhancement strategies.
American Psychological Association (APA)
Qu, Zhi& Xing, Yaqiong& Song, Yafei. 2019. Image Enhancement Based on Pulse Coupled Neural Network in the Nonsubsample Shearlet Transform Domain. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1194866
Modern Language Association (MLA)
Qu, Zhi…[et al.]. Image Enhancement Based on Pulse Coupled Neural Network in the Nonsubsample Shearlet Transform Domain. Mathematical Problems in Engineering No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1194866
American Medical Association (AMA)
Qu, Zhi& Xing, Yaqiong& Song, Yafei. Image Enhancement Based on Pulse Coupled Neural Network in the Nonsubsample Shearlet Transform Domain. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1194866
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194866