Title :
2D-SOFM Vector Quantization for Image Compression Based on Inverse Difference Pyramidal Decomposition
Author :
Hikal, Noha A. ; Kountchev, Roumen
Author_Institution :
Special Studies Acad., Cairo
Abstract :
In this paper a new developed algorithm for compression of still images based on 2D-SOFM NN´s in correspondence with the method of inverse difference pyramid (IDP) decomposition is represented. The new developed algorithm is well suited to be used in progressive image transmission (PIT). Advantage of the method relies on the learning process and adaptation capability of NN´s to reduce the matrices computation complexity and the total number of pyramid levels required for PIT. In addition to, for image reconstruction no interpolation is needed any more, which improves the quality of the reconstructed image
Keywords :
image coding; image reconstruction; vector quantisation; visual communication; 2D-SOFM vector quantization; image compression; image reconstruction; inverse difference pyramidal decomposition; learning process; progressive image transmission; Bit rate; Data structures; Discrete cosine transforms; Image coding; Image communication; Image reconstruction; Image resolution; Laplace equations; Spatial resolution; Vector quantization; Image Compression; Inverse Difference Pyramidal Decomposition; SOFM Neural Networks; Vector Quantization;
Conference_Titel :
Telecommunications in Modern Satellite, Cable and Broadcasting Services, 2005. 7th International Conference on
Conference_Location :
Nis
Print_ISBN :
0-7803-9164-0
DOI :
10.1109/TELSKS.2005.1572160
