Journal of the Korean Institute of Telematics and Electronics C (전자공학회논문지C)
- Volume 34C Issue 1
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- Pages.42-50
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- 1997
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- 1226-5853(pISSN)
Vector Quantization of Image Signal using Larning Count Control Neural Networks
학습 횟수 조절 신경 회로망을 이용한 영상 신호의 벡터 양자화
Abstract
Vector quantization has shown to be useful for compressing data related with a wide rnage of applications such as image processing, speech processing, and weather satellite. Neural networks of images this paper propses a efficient neural network learning algorithm, called learning count control algorithm based on the frquency sensitive learning algorithm. This algorithm can train a results more codewords can be assigned to the sensitive region of the human visual system and the quality of the reconstructed imate can be improved. We use a human visual systrem model that is a cascade of a nonlinear intensity mapping function and a modulation transfer function with a bandpass characteristic.
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