Improving Differently-Illuminant Images with Fuzzy Membership Based Saturation Weighting
June 2016
Gurpreet Kaur, Pooja Pooja, Varsha Sahni

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Improving Differently\u002DIlluminant Images with Fuzzy Membership Based Saturation Weighting Image
Abstract

Illumination estimation is basic to white balancing digital color images and to color constancy. The key to automatic white balancing of digital images is to estimate precisely the color of the overall scene illumination. Many methods for estimating the illumination's color has proposed. Though not the most exact, one of the simplest and quite extensively used methods are the gray world algorithm, white patch, max-RGB, Gray edge using first order derivative and gray edge using second order derivative, saturation weighting. The first-three methods have neglected the multiple light sources illuminate. In this work, we investigate how illuminate estimation techniques can be improved using fuzzy membership. The main aim of this paper is to evaluate performance of Fuzzy Enhancement based saturation weighting technique for different light sources (single, multiple, indoor scene and outdoor scene) under different conditions. The experiment has clearly shown the effectiveness of the proposed technique over the available methods.

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  • Eye Icon 71 views
  • Download Icon 19 downloads
Metrics Icon 71 views  //  19 downloads