Estimating illumination chromaticity via support vector regression

Xiong WH; Funt B

首页> 外文期刊>Journal of Imaging Science and Technology >Estimating illumination chromaticity via support vector regression

【24h】

Estimating illumination chromaticity via support vector regression

机译：通过支持向量回归估计照明色度

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

Support vector regression is applied to the problem of estimating the chromaticity of the light illuminating a scene from a color histogram of an image of the scene. Illumination estimation is fundamental to white balancing digital color images and to understanding human color constancy. Under controlled experimental conditions, the support vector method is shown to perform well. Its performance is compared to other published methods including neural network color constancy, color by correlation, and shades of gray. (C) 2006 Society for Imaging Science and Technology.

机译：支持向量回归被应用于从场景的图像的颜色直方图估计照明场景的光的色度的问题。照明估计对于白平衡数字彩色图像和理解人的色彩稳定性至关重要。在控制的实验条件下，支持向量法显示出良好的性能。将其性能与其他已发布的方法进行了比较，这些方法包括神经网络的颜色恒定性，相关色和灰色阴影。（C）2006年影像科学与技术学会。

著录项

来源
《Journal of Imaging Science and Technology》 |2006年第4期|p. 341-348|共8页
作者
Xiong WH; Funt B;
展开▼
作者单位

Simon Fraser Univ, Sch Comp Sci, Vancouver, BC, Canada;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类摄影技术;
关键词
COLOR CONSTANCY ALGORITHMS; MACHINES;

机译：颜色一致性算法;机器;

相似文献

外文文献
中文文献
专利

1. Combinational illumination estimation method based on image-specific PCA filters and support vector regression [J] . Martin Šave, Božidar Potočnik Machine Vision and Applications . 2018,第1期

机译：基于图像专用PCA滤波器和支持向量回归的组合照度估计方法
2. Illumination compensation in textile colour constancy, based on an improved least-squares support vector regression and an improved GM(1,1) model of grey theory [J] . Zhang Jian-xin, Zhang Pan, Wu Xiao-liang, Coloration Technology . 2017,第2期

机译：基于改进的最小二乘支持向量回归和改进的GM（1,1）灰色理论模型，实现纺织品颜色恒定的照明补偿
3. Zoned elasticity modulus inversion analysis method of a high arch dam based on unconstrained Lagrange support vector regression (support vector regression arch dam) [J] . Chungao Liu, Chongshi Gu, Bo Chen Engineering with Computers . 2017,第3期

机译：基于无约束拉格朗日支持向量回归的高拱坝分区弹性模量反演分析方法（支持向量回归拱门）
4. Estimating Illumination Chromaticity via Support Vector Regression [C] . Brian Funt, Weihua Xiong Color Imaging Conference: Color Science and Engineering: Systems, Technologies, Applications; 20041109-12; Scottsdale,AZ(US) . 2004

机译：通过支持向量回归估计照明色度
5. Adaptive Least Squares Support Vector Regression for History Matching and Markov Chain Monte Carlo Uncertainty Quantification [D] . Sousa, Emilio Paulo dos Santos. 2019

机译：自适应最小二乘支持历史匹配和马尔可夫链蒙特卡罗不确定性量化的向量回归
6. Development of a predictive model for estimating the specific heat capacity of metallic oxides/ethylene glycol-based nanofluids using support vector regression [O] . Ibrahim Olanrewaju Alade, Mohd Amiruddin Abd Rahman, Aliyu Bagudu, 2019

机译：使用支持向量回归法预测金属氧化物/乙二醇基纳米流体比热容的预测模型的开发
7. Estimating Illumination Chromaticity Via Support Vector Regression [O] . Weihua Xiong, Brian Funt 2006

机译：通过支持向量回归估计照明色度
8. Vector-Valued Support Vector Regression [R] . Brudnak, M. 2006

机译：矢量值支持向量回归

Estimating illumination chromaticity via support vector regression

摘要

著录项

相似文献

相关主题

期刊订阅