JOURNAL ARTICLE

Multiresolution segmentation-based image coding with hierarchical data structures

Abstract

This paper presents two multiresolution segmentation-based algorithms for low bit rate image compression using hierarchical data structures. The segmentation is achieved with quadtree and binary space partitioning tree hierarchical data structures and the encoding is performed by using the projection pursuit (matching pursuit) with a finite dictionary of spline functions with various degrees of smoothness. Comparison with JPEG at rates below 0.5 bit/pixel shows superior performance both in terms of peak signal-to-noise ratio (PSNR) and subjective image quality.

Keywords:
Quadtree Artificial intelligence Computer science Computer vision Image segmentation Segmentation JPEG Scale-space segmentation Pattern recognition (psychology) Data compression Pixel Spline (mechanical) Peak signal-to-noise ratio Image (mathematics)

Metrics

15
Cited By
1.36
FWCI (Field Weighted Citation Impact)
22
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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