软件学报
軟件學報
연건학보
JOURNAL OF SOFTWARE
2004年
5期
676-688
,共13页
张淮峰%Jan Cech%Radim Sara%吴福朝%胡占义
張淮峰%Jan Cech%Radim Sara%吳福朝%鬍佔義
장회봉%Jan Cech%Radim Sara%오복조%호점의
图像校正%射影畸变%基本矩阵
圖像校正%射影畸變%基本矩陣
도상교정%사영기변%기본구진
image rectification%projective distortion%fundamental matrix
主要讨论两方面的工作.首先,对三视校正问题进行理论分析,给出了校正后图像的基本矩阵与其约束条件之间的关系,讨论了三视校正过程中的6个自由参数的几何含义.这些结果为处理校正过程中带来的图像射影畸变提供了理论根据.其次,在RANSAC(random sampling consensus)框架下,提出了一种鲁棒的三视校正算法.与传统的校正算法不同,该算法不再只依赖于基本矩阵,而是直接利用了原始匹配点的信息.这种基于点的方法有两个优点:一方面,由于噪声的干扰,基本矩阵往往估计得不够准确;另一方面,由于基本矩阵的评价准则与校正结果的评价准则不同,即使从好的基本矩阵出发,也未必能获得好的校正结果.大量的模拟和真实图像实验表明,该算法具有很强的抗噪声及抗错误匹配的能力,能够获得令人满意的校正效果.
主要討論兩方麵的工作.首先,對三視校正問題進行理論分析,給齣瞭校正後圖像的基本矩陣與其約束條件之間的關繫,討論瞭三視校正過程中的6箇自由參數的幾何含義.這些結果為處理校正過程中帶來的圖像射影畸變提供瞭理論根據.其次,在RANSAC(random sampling consensus)框架下,提齣瞭一種魯棒的三視校正算法.與傳統的校正算法不同,該算法不再隻依賴于基本矩陣,而是直接利用瞭原始匹配點的信息.這種基于點的方法有兩箇優點:一方麵,由于譟聲的榦擾,基本矩陣往往估計得不夠準確;另一方麵,由于基本矩陣的評價準則與校正結果的評價準則不同,即使從好的基本矩陣齣髮,也未必能穫得好的校正結果.大量的模擬和真實圖像實驗錶明,該算法具有很彊的抗譟聲及抗錯誤匹配的能力,能夠穫得令人滿意的校正效果.
주요토론량방면적공작.수선,대삼시교정문제진행이론분석,급출료교정후도상적기본구진여기약속조건지간적관계,토론료삼시교정과정중적6개자유삼수적궤하함의.저사결과위처리교정과정중대래적도상사영기변제공료이론근거.기차,재RANSAC(random sampling consensus)광가하,제출료일충로봉적삼시교정산법.여전통적교정산법불동,해산법불재지의뢰우기본구진,이시직접이용료원시필배점적신식.저충기우점적방법유량개우점:일방면,유우조성적간우,기본구진왕왕고계득불구준학;령일방면,유우기본구진적평개준칙여교정결과적평개준칙불동,즉사종호적기본구진출발,야미필능획득호적교정결과.대량적모의화진실도상실험표명,해산법구유흔강적항조성급항착오필배적능력,능구획득령인만의적교정효과.
The main contributions are two-fold: Firstly, some theoretical analyses are carried out on trinocular rectification, including the relationship among the three rectified images and their three fundamental matrices, and an geometric interpretation of the 6 free parameters involved in the rectification process. Such results could be used as a theoretical guide to reduce the induced projective distortion. Secondly, under the RANSAC (random sampling consensus) paradigm, a robust trinocular rectification algorithm is proposed. Unlike the traditional ones where only the fundamental matrices are used to rectify images, this algorithm instead uses directly corresponding points for the rectification. The main advantage of this point-based approach is that on one hand, the computation of fundamental matrices is usually prone to noise; on the other hand, good fundamental matrices do not necessarily always produce good rectified images because the two processes have different evaluation criteria. Extensive simulation and experiments with real images show that the proposed rectification technique is resistant to noise as well as to outliers of the corresponding points, and fairly good rectification results can be obtained.