A MSB-biased self-organizing feature map for still color image compression

Author

Chang, Chip-Hong ; Xiao, Rui ; Srikanthan, Thambipillai

Author_Institution

Centre for High Performance Embedded Syst., Nanyang Technol. Univ., Singapore, Singapore

Volume

2

fYear

2002

fDate

2002

Firstpage

85

Abstract

A novel most significant bit (MSB) biased self organizing feature map (SOFM) algorithm, suitable for VLSI implementation, has been proposed for digital still color image compression. By encoding each pixel´s RGB values with a negative 128 bias and presenting only its least significant 7-bit magnitude to the SOFM network, 3 to 6 dB improvement in PSNR can be achieved in the reconstructed images. Based on this new encoding scheme, which requires only a simple selective complementation, the entire SOFM network can be significantly scaled down without severely scarifying the visual quality of the displayed images.

Keywords

image coding; image colour analysis; image reconstruction; self-organising feature maps; vector quantisation; MSB-biased Kohonen SOFM algorithms; PSNR improvement; VLSI implementation; digital still color image compression; displayed image visual quality; image reconstruction; most significant bit biased self-organizing feature maps; negative bias pixel RGB value encoding; pixel magnitude; selective complementation scheme; vector quantization; Color; Costs; Embedded system; Hardware; Humans; Image coding; Image reconstruction; Pixel; Vector quantization; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2002. APCCAS '02. 2002 Asia-Pacific Conference on

Print_ISBN

0-7803-7690-0

Type

conf

DOI

10.1109/APCCAS.2002.1115129

Filename

1115129