Abstract
In this paper a new algorithm for image compression, named predictive vector quantization (PVQ), is developed based on competitive neural networks quantizer and neural networks predictor. The modified closed-loop PVQ methodology is developed. The experimental results are presented and the performance of the algorithm is discussed. A comparison of two feed-forward neural network structures applied for predictor is discussed. © Springer-Verlag Berlin Heidelberg 2004.
Cite
CITATION STYLE
Cierniak, R. (2004). Image compression based on soft computing techniques. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3019, 609–617. https://doi.org/10.1007/978-3-540-24669-5_80
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