IMAGE PREDICTIVE VECTOR CODING USING NEURAL NET WORX WITH NEW TRAINING
EL-Fishawy, A., Atta, R., Hadhoud, M., Awadalla, K. (1993). IMAGE PREDICTIVE VECTOR CODING USING NEURAL NET WORX WITH NEW TRAINING. EKB Journal Management System, 5(ASAT CONFERENCE 4 - 6 May 1993, CAIRO), 487-508. doi: 10.21608/asat.1993.25651
A. S. EL-Fishawy; R. M. Atta; M. Hadhoud; K. H. Awadalla. "IMAGE PREDICTIVE VECTOR CODING USING NEURAL NET WORX WITH NEW TRAINING". EKB Journal Management System, 5, ASAT CONFERENCE 4 - 6 May 1993, CAIRO, 1993, 487-508. doi: 10.21608/asat.1993.25651
EL-Fishawy, A., Atta, R., Hadhoud, M., Awadalla, K. (1993). 'IMAGE PREDICTIVE VECTOR CODING USING NEURAL NET WORX WITH NEW TRAINING', EKB Journal Management System, 5(ASAT CONFERENCE 4 - 6 May 1993, CAIRO), pp. 487-508. doi: 10.21608/asat.1993.25651
EL-Fishawy, A., Atta, R., Hadhoud, M., Awadalla, K. IMAGE PREDICTIVE VECTOR CODING USING NEURAL NET WORX WITH NEW TRAINING. EKB Journal Management System, 1993; 5(ASAT CONFERENCE 4 - 6 May 1993, CAIRO): 487-508. doi: 10.21608/asat.1993.25651

IMAGE PREDICTIVE VECTOR CODING USING NEURAL NET WORX WITH NEW TRAINING

International Conference on Aerospace Sciences and Aviation Technology
Article 41, Volume 5, ASAT CONFERENCE 4 - 6 May 1993, CAIRO, May 1993, Page 487-508  XML PDF (5.9 MB)
Document Type: Original Article
DOI: 10.21608/asat.1993.25651
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Authors
A. S. EL-Fishawy1; R. M. Atta2; M. Hadhoud3; K. H. Awadalla4
1Assistant Prof., Faculty of Electronic Engineering, Comm. Eng. Dept., Menouf. Egypt.
2Assistant Lecturer., Faculty of Electronic Engineering, Comm. Eng. Dept., Menouf. Egypt.
3Associate Prof., Faculty of Electronic Engineering, Comm. Eng. Dept., Menouf. Egypt.
4Prof., Faculty of Electronic Engineering, Comm. Eng. Dept., Menouf. Egypt.
Abstract
Image data compression is used to reduce the transmission rates or the amount of informatipn to be sent or stored without greatly affecting the quality of the reconstructed images. Many techniques, such as vector quantization, have been used in'order to satisfy these requirements. Using the neural network techniques, rather than the traditional technique in this subject decreases the loss of image information and hence enhances its quality specially at low bit rates.
Some of the neural network models proposed for image data compression still have some defects specially, when the actual images are not included in the training phase of the network. In this paper a new training set is proposed to be used in the training set of the Kohonen self-organizing map when it used in image data compression applications to increase its efficiency. This proposed training set is statistically dependent with all images independent of their types. A predictive vector quantization using both Kohonen self-organizing map and the adaptive differential pulse code modulation with the linear neural network predictor is also introduced. The simulation results':this paper show that the performance of the proposed techniques is much better than that used by others.
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