Title :
Adaptive vector quantisation of non-orthogonal representations for image compression
Author :
Mikhael, W.B. ; Ragothaman, P.
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
fDate :
1/23/2003 12:00:00 AM
Abstract :
An efficient compression technique employing adaptive vector quantisation of multiple non-orthogonal transform domain representations of still images is developed. For each sub-image, the encoder selects a code from the domain that yields best representation. The performance improvement employing the proposed technique relative to existing single domain vector quantisation coding methods, for the same compression ratio, is obtained at the expense of increased computational complexity.
Keywords :
adaptive signal processing; computational complexity; image coding; image reconstruction; image representation; vector quantisation; adaptive vector quantisation; compression ratio; computational complexity; encoder; image compression; multiple nonorthogonal transform domain representations; nonorthogonal representations; performance improvement; reconstructed images; still images;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20030139