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논문검색

Medical Image Fusion based on Pulse Coupled Neural Network Combining with Compressive Sensing

초록

영어

Image fusion is an important branch of information fusion, widely used in various fields, especially in medical field. So increasing the quality and efficiency of medical image fusion has great significance. Combining the advantages of pulse coupled neural networks with Compressive Sensing; this paper puts forward a novel image fusion method in NSCT transform domain. First, NSCT transform is applied to the source images, and the coefficients in low frequency coefficient are fused by mean rules. For high frequency coefficient, CS is applied and PCNN. Finally, inverse NSCT is applied to get the reconstructed image. The experimental results show that the fusion algorithm proposed in this paper in the performance and integration efficiency has better fusion results.

목차

Abstract
 1. Introduction
 2. Principles of CS
 3. Basic Theory of PCNN
 4. Medical Image Fusion based on Compressive Sensing and Pulse Coupled Neural Network
  4.1 Fusion of Low Frequency Subband Coefficients
  4.2 Fusion of High Frequency Subband Coefficients
 5. Experiments and Results Analysis
 6. Conclusion
 References

키워드

저자정보

  • AiliWang Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin, China
  • Jiaying Zhao Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin, China
  • Shiyu Dai Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin, China
  • Yuji Iwahori Dept. of Computer Science, Chubu University, Japan
  • Yangyang Zhao Dept. of Computer Science, Chubu University, Japan

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