Parallax correction via disparity estimation in a multi-aperture camera

Tutkimustuotos: Lehtiartikkeli

Tutkijat

Organisaatiot

  • University of Oulu

Kuvaus

In this paper, an image fusion algorithm is proposed for a multi-aperture camera. Such camera is a feasible alternative to traditional Bayer filter camera in terms of image quality, camera size and camera features. The camera consists of several camera units, each having dedicated optics and color filter. The main challenge of a multi-aperture camera arises from the fact that each camera unit has a slightly different viewpoint. Our image fusion algorithm corrects the parallax error between the sub-images using a disparity map, which is estimated from the single-spectral images. We improve the disparity estimation by combining matching costs over multiple views using trifocal tensors. Images are matched using two alternative matching costs, mutual information and Census transform. We also compare two different disparity estimation methods, graph cuts and semi-global matching. The results show that the overall quality of the fused images is near the reference images.

Yksityiskohdat

AlkuperäiskieliEnglanti
Sivut1313-1323
Sivumäärä11
JulkaisuMACHINE VISION AND APPLICATIONS
Vuosikerta27
Numero8
Varhainen verkossa julkaisun päivämäärä25 toukokuuta 2016
TilaJulkaistu - marraskuuta 2016
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

ID: 4458234