The human color sensation depends on the spatial distribution of the colors in the viewed scene. This principle is at the basis of the Random Spray Retinex (RSR) algorithm. In this work, we modify RSR by integrating its approach with a method to weight and tune the locality of spatial image information. This modification allows a spatial control of the local effect of RSR on image color filtering. We study the performances of this spatially weighted version of RSR on a public image dataset by analyzing and comparing several image features of the output image and its local properties.

Tuning the locality of filtering with a spatially weighted implementation of random spray Retinex

Lecca, Michela;
2015

Abstract

The human color sensation depends on the spatial distribution of the colors in the viewed scene. This principle is at the basis of the Random Spray Retinex (RSR) algorithm. In this work, we modify RSR by integrating its approach with a method to weight and tune the locality of spatial image information. This modification allows a spatial control of the local effect of RSR on image color filtering. We study the performances of this spatially weighted version of RSR on a public image dataset by analyzing and comparing several image features of the output image and its local properties.
File in questo prodotto:
File Dimensione Formato  
document.pdf

non disponibili

Licenza: NON PUBBLICO - Accesso privato/ristretto
3.34 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

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: http://hdl.handle.net/11582/300719
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact