JOURNAL ARTICLE

<title>Vector quantization based on a psychovisual lattice for a visual subband coding scheme</title>

Hakim SenaneAbdelhakim SaadaneDominique Barba

Year: 1997 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3024 Pages: 459-467   Publisher: SPIE

Abstract

A vector quantization based on a psychovisual lattice is used in a visual components image coding scheme to achieve a high compression ratio with an excellent visual quality. The vectors construction methodology preserves the main properties of the human visual system concerning the perception of quantization impairments and takes into account the masking effect due to interaction between subbands with the same radial frequency but with different orientations. The vectors components are the local band limited contrasts Cij defined as the ratio between the luminance Lij at point, which belongs to the radial subband i and angular sector j, and the average luminance at this location corresponding to the radial frequencies up to subband i-1. Hence the vectors dimension is depending on the orientation selectivity of the chosen decomposition. The low pass subband, which is nondirectional is scalar quantized. The performances of the coding scheme have been evaluated on a set of images in terms of peak SNR, true bit rates and visual quality. For this, no impairments are visible at a distance of 4 times the height of a high quality TV monitor. The SNR are about 6 to 8 dB under the ones of classical subband image coding schemes when producing the same visual quality. Due to the use of the local band limited contrast, the particularity of this approach relies in the structure of the reconstruction image error which is found to be highly correlated to the structure of the original image.

Keywords:
Luminance Vector quantization Computer science Human visual system model Computer vision Sub-band coding Quantization (signal processing) Artificial intelligence Coding (social sciences) Image quality Spatial frequency Mathematics Algorithm Optics Physics Image (mathematics)

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Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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