Title :
Image compression with hardware self-organizing map
Author :
Hikawa, Hiroomi ; Doumoto, Kenji ; Miyoshi, Seiji ; Maeda, Yutaka
Author_Institution :
Fac. of Eng. Sci., Kansai Univ., Suita, Japan
Abstract :
This paper discusses the use of self-organizing map (SOM) in the image coding. The image is partitioned into blocks each of which is fed to the SOM as the training vectors. Then they are quantized into smaller number of vectors that is used as codeword to reconstruct the image. Thus the data size is reduced. In reconstructing the image, each block is filled with the corresponding codeword. The feasibility of the system is tested by computer simulations and the effect of the sizes of blocks and SOM on the compression rate and image quality is studied. Then the SOM based hardware image coding system is designed, and its functionality is also tested. It is estimated that the hardware SOM can code a single image within 1.2 ms.
Keywords :
data compression; image coding; image reconstruction; self-organising feature maps; hardware self-organizing map; image coding; image compression; image quality; image reconstruction; time 1.2 ms; training vectors; Hardware; Image coding; Image reconstruction; Indexes; Neurons; Pixel; Quantization;
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6916-1
DOI :
10.1109/IJCNN.2010.5596473
