Open AccessConfocal microscopic image sequence compression using vector quantization and three‐dimensional pyramid
Author(s) -
Cockshott W. Paul,
Tao Yegang,
Ao Gang,
Balch Peter,
Briones Ana M.,
Daly Craig
Publication year - 2003
Publication title -
scanning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1932-8745
pISSN - 0161-0457
DOI - 10.1002/sca.4950250506
Subject(s) - pyramid (geometry) , confocal , artificial intelligence , computer vision , vector quantization , volume (thermodynamics) , computer science , confocal laser scanning microscopy , image compression , quantization (signal processing) , gas compressor , image processing , image (mathematics) , pattern recognition (psychology) , optics , biomedical engineering , physics , engineering , quantum mechanics , thermodynamics
The three‐dimensional (3‐D) pyramid compressor project at the University of Glasgow has developed a compressor for images obtained from confocal laser scanning microscopy (CLSM) device. The proposed method using a combination of image pyramid coder and vector quantization techniques has good performance at compressing confocal volume image data. An experiment was conducted on several kinds of CLSM data using the presented compressor compared with other well‐known volume data compressors, such as MPEG‐1. 1 The results showed that the 3‐D pyramid compressor gave a higher subjective and objective image quality of reconstructed images at the same compression ratio, and presented more acceptable results when applying image processing filters on reconstructed images.