A new color quantization algorithm, CQ, is presented, which includes two phases. The first phase reduces the number of colors by reducing the spatial resolution of the input image. The second phase furthermore reduces the number of colors by performing color clustering guided by distance information. Then, color mapping completes the process. The algorithm has been tested on a large number of color images with different size and color distribution, and the performance has been compared to the performance of other algorithms in the literature.

Spatial Resolution and Distance Information for Color Quantization

G Ramella;G Sanniti di Baja
2013

Abstract

A new color quantization algorithm, CQ, is presented, which includes two phases. The first phase reduces the number of colors by reducing the spatial resolution of the input image. The second phase furthermore reduces the number of colors by performing color clustering guided by distance information. Then, color mapping completes the process. The algorithm has been tested on a large number of color images with different size and color distribution, and the performance has been compared to the performance of other algorithms in the literature.
2013
Istituto Applicazioni del Calcolo ''Mauro Picone''
Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello" - ISASI
978-3-642-41183-0
Color Quantization
Image Scaling
Distance Transform
Voronoi Diagram
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/215268
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact