Color re-indexing is one of main approaches for improving the loss-less compression of color indexed images. Zero-order entropy reduction of indexes matrix is the key to obtain high compression ratio. However, obtaining the optimal re-indexed palette is a challenging problem that cannot be solved by brute-force approaches. In this paper we propose a novel re-indexing approach where the Travelling Salesman Problem is solved through Ant Colony Optimization. Our method is proved to achieve high quality results by outperforming state-of-art ones in term of compression gain. Additionally, we exploit clustering and GPU computing to make our solution extremely fast.

A FAST PALETTE REORDERING TECHNIQUE BASED ON GPU-OPTIMIZED GENETIC ALGORITHMS

Giudice, O;Allegra, D;Stanco, F;Battiato, S
2018

Abstract

Color re-indexing is one of main approaches for improving the loss-less compression of color indexed images. Zero-order entropy reduction of indexes matrix is the key to obtain high compression ratio. However, obtaining the optimal re-indexed palette is a challenging problem that cannot be solved by brute-force approaches. In this paper we propose a novel re-indexing approach where the Travelling Salesman Problem is solved through Ant Colony Optimization. Our method is proved to achieve high quality results by outperforming state-of-art ones in term of compression gain. Additionally, we exploit clustering and GPU computing to make our solution extremely fast.
Image coding; Ant Colony Optimization; Entropy; Color; Data compression
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/361904
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