A Method of Non-textured Regions Matching

It is difficult for existing dense or quasidense matching algorithms to obtain accurate matching results due to the lack of effective feature information in non-textured regions. This may affect the quality of subsequent 3D reconstruction and super-resolution reconstruction. We propose a method of non-textured regions matching. To reduce the impact of noise and illumination, vector sampling normalized cross correlation is proposed to directly measure coherence between two colour images by the effective information of multi-channel features. Three mathematical properties are used in affine transformation: 1) Centroid location is not affected by affine transformation; 2) Affine transformation transforms a straight line into another straight line; 3) Affine transformation maintains the linear relation invariant. In non-textured regions, we can construct texture regions which have affine invariant properties to improve the accuracy of template matching. This could provide more information for the diffusion of dense or quasi-dense matching. In experiments, we demonstrate that the method has high accuracy in cases where there is no big distortion between the two viewing angles from two aspects of simulated images and photographic images.