Measurement of Minimum Resolvable Contrast Based on BP Neural Network

Wang Yun; Li Wenjuan; Liu Jie; Yu Yong

Measurement of Minimum Resolvable Contrast Based on BP Neural Network

원문정보

보안공학연구지원센터(IJSIP) International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.6 No.6 2013.12 pp.51-58

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초록

영어

Aiming at the MTF evaluation limitations in visible imaging system, this paper introduces the minimum resolvable contrast. On the basis of MRC theoretical, the paper obtains subjective and objective methods of MRC measurement. Then MRC measurement based on neural network is put forward, which does not depend on subjective judgment of person. BP neural network is established and trained. Therefore, the network can replace human eyes to judge test patterns with different spatial frequencies and contrasts. Sony camera with 500 megapixels is selected in the experiment. Results show that MRC values of the objective measurement at all frequencies are less than those of the subjective measurement. The MRC Measurement has good stability.

Abstract
1. Introduction
2. Theory of Measuring MRC
  2.1. Principle
  2.2. Method of Measuring MRC
3. MRC measurement by Neural Network
  3.1. Neural Network
  3.2. BP Neural Network Model
  3.3. Image Processing
  3.4. Feature Extraction
  3.5. Image of MRC Recognition
4. Measurement Experiment and Results
5. Conclusions
Acknowledgements
References

키워드

저자정보

Wang Yun School of Electrical and Electronic Engineering Harbin University of Science &Technology Harbin, China
Li Wenjuan School of Electrical and Electronic Engineering Harbin University of Science &Technology Harbin, China
Liu Jie School of Electrical and Electronic Engineering Harbin University of Science &Technology Harbin, China
Yu Yong School of Electrical and Electronic Engineering Harbin University of Science &Technology Harbin, China

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