New stereo vision matching algorithm based on constrained dynamic programming and higher order statistics criteria

• Autorzy: Rziza M. , Aboutajdine D.
• Języki publikacji: EN

Abstrakty

EN

We present a new efficient stereo algorithm addressing robust disparity estimation in the presence of noise. We propose hare a new constrained dynamic programming algorithm based on Higher Order Statistics (HOS) criteria for matching noisy images. Experiments with both synthetic and noisy real images have validated our method and have clearly shown the improvement over the existing ones. The obtained dense disparity map is more reliable when compared to the similar Second-Order Statistics (SOS) based constrained dynamic programming and HOS-based correlation methods.

Słowa kluczowe

EN

rectification; disparity; matching; correlation; dynamic programming; constrained dynamic programming; higher order statistics; cumulant

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2001
• Tom: Vol. 10, No. 3
• Strony: 317--331
• Opis fizyczny: Bibliogr. 16 poz.

Twórcy

autor

Rziza M.

autor

Aboutajdine D.

• GSCM-LEESA, B.P. 1014, Science Faculty of Rabat, Marocco,