Neural Architectures for Correlated Noise Removal in Image Processing
المؤلفون المشاركون
Cocianu, Catalina
Stan, Alexandru
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-04-19
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
The paper proposes a new method that combines the decorrelation and shrinkage techniques to neural network-based approaches for noise removal purposes.
The images are represented as sequences of equal sized blocks, each block being distorted by a stationary statistical correlated noise.
Some significant amount of the induced noise in the blocks is removed in a preprocessing step, using a decorrelation method combined with a standard shrinkage-based technique.
The preprocessing step provides for each initial image a sequence of blocks that are further compressed at a certain rate, each component of the resulting sequence being supplied as inputs to a feed-forward neural architecture FX→FH→FY.
The local memories of the neurons of the layers FH and FY are generated through a supervised learning process based on the compressed versions of blocks of the same index value supplied as inputs and the compressed versions of them resulting as the mean of their preprocessed versions.
Finally, using the standard decompression technique, the sequence of the decompressed blocks is the cleaned representation of the initial image.
The performance of the proposed method is evaluated by a long series of tests, the results being very encouraging as compared to similar developments for noise removal purposes.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Cocianu, Catalina& Stan, Alexandru. 2016. Neural Architectures for Correlated Noise Removal in Image Processing. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1112417
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Cocianu, Catalina& Stan, Alexandru. Neural Architectures for Correlated Noise Removal in Image Processing. Mathematical Problems in Engineering No. 2016 (2016), pp.1-14.
https://search.emarefa.net/detail/BIM-1112417
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Cocianu, Catalina& Stan, Alexandru. Neural Architectures for Correlated Noise Removal in Image Processing. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1112417
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1112417
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