Improving reflectance estimation by BRDF-consistent region clustering

作     者：LIN Steve 

作者机构：Beijing 100080 China Visual Computing Group Microsoft Research Asia 

出 版 物：《Progress in Natural Science:Materials International》 (自然科学进展·国际材料(英文))

年 卷 期：2006年第16卷第3期

页      面：313-320页

核心收录：

学科分类：08[工学] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by National Natural Science Foundation of China (Key Program) (Grant No. 60333010) National Natural Science Foundation for Innovation Research Groups (Grant No. 60021201) the Major State Basic Research Development Program of China (Grant No. 2002CB312102) 

主　　题：texture shading grouping and segmentation reflectance estimation BRDF uncertainty. 

摘      要：Previous studies in reflectance estimation generally require prior segmentation of an image into regions of uniform reflectance. Due to the measurement noise and limited sampling of the BRDF (bi-directional reflectance function) directions, such estimated results of reflectance are not accurate. In this paper, we propose a novel method for reducing uncertainty in reflectance estimates by merging image regions which have consistent reflectance observations. Each image region acts as a reflectance subspace, so merging of the image regions can result in subspace reduction. We propose a Bayesian segmentation framework to decrease the reflectance uncertainty by using novel merging criteria. Finally, a maximum likelihood reflectance estimation is made for each resulting image region. Experimental results verify the feasibility and superiority of this reflectance-oriented region merging method.