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

Civil Engineering

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