Title :
CNN-based image predictive coding
Author :
Tang Tang ; Tetzlaff, Ronald
Author_Institution :
Fac. of Electr. Eng & Inf. Technol., Tech. Univ. Dresden, Dresden, Germany
Abstract :
In this work the feasibility of implementing Cellular Neural Networks (CNN) for image predictive coding is investigated. Various CNN structures as predictors are proposed. The performances are compared to the existing predictive coding methods. Thanks to their massive parallel nature, CNN have been proven well suitable for image predictive coding application.
Keywords :
cellular neural nets; image coding; CNN structures; cellular neural networks; image predictive coding application; massive parallel nature; predictive coding methods; Complexity theory; Image coding; Nonhomogeneous media; Polynomials; Predictive coding; Standards; Cellular Neural Networks; predictive coding;
Conference_Titel :
Cellular Nanoscale Networks and their Applications (CNNA), 2014 14th International Workshop on
Conference_Location :
Notre Dame, IN
DOI :
10.1109/CNNA.2014.6888631
