Blur and Contrast Invariant Fast Stereo Matching

We propose a novel approach for estimating a depth-map from a pair of rectified stereo images degraded by blur and contrast change. At each location in image space, information is encoded with a new class of descriptors that are invariant to convolution with centrally symmetric PSF and to variations in contrast. The descriptors are based on local-phase quantization, they can be computed very efficiently and encoded in a limited number of bits. A simple measure for comparing two encoded templates is also introduced. Results show that, the proposed method can represent a cheap but still effective way for estimating disparity maps from degraded images, without making restrictive assumptions; these advantages make it attractive for practical applications.

• Type: Conference
• Year: 2008
• Where: ACIVS
• Authors: Matteo Pedone, Janne Heikkilä
• Keywords: ACIVS 2008, Computer Vision, Contrast Change, Encoded Templates, Symmetric Psf