Open AccessAn Improved White Patch Method for Image Illumination Estimation
Author(s) -
Li Zhao,
Wei Ma,
Mengxia Tang,
Songnan Chen
Publication year - 2020
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.156
H-Index - 13
ISSN - 1998-4464
DOI - 10.46300/9106.2020.14.76
Subject(s) - artificial intelligence , computer vision , rgb color model , computer science , image (mathematics) , kernel density estimation , color balance , kernel (algebra) , window (computing) , constraint (computer aided design) , color image , pixel , mathematics , pattern recognition (psychology) , image processing , statistics , geometry , combinatorics , estimator , operating system
As one of the underlying pixel-based illumination estimation algorithms, the White Patch algorithm is an algorithm for calculating the global illumination RGB value of an image based on the specific assumption that the maximum reflected light on the scene is chromatic. The algorithm is harsh on the assumptions of scene illumination, and many images are difficult to satisfy this assumption constraint. In this paper, we propose an improved White Patch image illumination estimation method. Firstly, the image patch is extracted by using sliding window method, we then use the white patch algorithm to estimate the illumination color value of each patch, and finally the kernel density estimation is adopted to obtain the overall illumination color value of the image. The experimental results show that the improved White Patch images illumination estimation method proposed to this paper performs better on the illumination estimation of natural illumination scene images.