Medical Image Fusion Based on Fast Finite Shearlet Transform and Sparse Representation
المؤلفون المشاركون
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-03-03
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Clinical diagnosis has high requirements for the visual effect of medical images.
To obtain rich detail features and clear edges for fusion medical images, an image fusion algorithm FFST-SR-PCNN based on fast finite shearlet transform (FFST) and sparse representation is proposed, aiming at the problem of poor clarity of edge details that is conducive to maintaining the details of source image in current algorithms.
Firstly, the source image is decomposed into low-frequency coefficients and high-frequency coefficients by FFST.
Secondly, the K-SVD method is used to train the low-frequency coefficients to obtain the overcomplete dictionary D, and then the OMP algorithm sparsely encodes the low-frequency coefficients to complete the fusion of the low-frequency coefficients.
Then, a high-frequency coefficient is applied to excite a pulse-coupled neural network, and the fusion coefficient of the high-frequency coefficient is selected according to the number of ignitions.
Finally, the fused low-frequency coefficient and high-frequency coefficient are reconstructed into the fused medical image by FFST inverse transform.
The experimental results show that the image fusion result of the proposed algorithm is about 35% higher than the comparison algorithms for the edge information transfer factor QAB/F index and has achieved good results in both subjective visual effects and objective evaluation indicators.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Tan, Ling& Yu, Xin. 2019. Medical Image Fusion Based on Fast Finite Shearlet Transform and Sparse Representation. Computational and Mathematical Methods in Medicine،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1130536
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Tan, Ling& Yu, Xin. Medical Image Fusion Based on Fast Finite Shearlet Transform and Sparse Representation. Computational and Mathematical Methods in Medicine No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1130536
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Tan, Ling& Yu, Xin. Medical Image Fusion Based on Fast Finite Shearlet Transform and Sparse Representation. Computational and Mathematical Methods in Medicine. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1130536
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1130536
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر