Title :
Neural clustering for optimal KLT image compression
Author :
Martinelli, G. ; Ricotti, L. Prina ; Marcone, G.
Author_Institution :
Dipartimento INFOCOM, Rome Univ., Italy
fDate :
4/1/1993 12:00:00 AM
Abstract :
A multiple class approach is proposed for improving the performance of the Karhunen-Loeve transform (KLT) image compression technique. The classification is adaptively performed by suitable neural networks. Several examples are presented in order to show that the proposed method performs much better than the classical discrete cosine transform (DCT)
Keywords :
data compression; image processing; neural nets; transforms; DCT; KLT; Karhunen-Loeve transform; discrete cosine transform; image classification; image compression; neural clustering; neural networks; Discrete cosine transforms; Discrete transforms; Image coding; Image reconstruction; Karhunen-Loeve transforms; Mean square error methods; Multilayer perceptrons; Neural networks; Neurons; Pixel;
Journal_Title :
Signal Processing, IEEE Transactions on
