Multiwavelet Evaluation for Stereo Correspondence

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Stereopsis, the process of extracting depth information from stereoscopic images, has multiple practical applications in its discrete form, ranging from entertainment, broadcasting, 3D modelling and visualisation to robotics and automated industrial inspection, just to name a few. Calculating the disparity between the left and right stereo images - aka stereo correspondence matching - is the most challenging stage in stereopsis applications. Biologically, the human brain achieves this task by employing a multichannel, multiresolution mechanism, recognising the fact that natural visual scenes contain detail information in several resolutions. Discrete stereopsis can be carried out both in the spatial domain and the frequency domain. Spatial image processing techniques offer perfect localisation in space but no localisation in frequency. Traditional image transforms achieve perfect localisation in frequency but no (or very poor) spatial localisation. Wavelets were the first modern transform to offer a hierarchical, multiresolution approach, which combines the best of both worlds: a space-frequency hierarchical multiresolution decomposition of the original image, with both local and global spatial support (section 2.3). They rapidly became a popular choice for stereo correspondence. To achieve optimal performance in the context of stereo correspondence, a wavelet should ideally simultaneously posses the following properties: orthogonality, locality (i.e. compact support, smooth filters and a large number of vanishing moments) and symmetry. Unfortunately a wavelet can never possess all these features simultaneously. Fortunately, this is not the case for multiwavelets, a relatively new, multichannel competitor of the (scalar) wavelets. In spite of the fact that application-wise multiwavelets are a rather under-researched topic, they have been already proven to perform better than scalar wavelets in many applications. Furthermore, there are different types of multiwavelets available: separable vs nonseparable, balanced vs unbalanced, symmetric-symmetric vs symmetric-antisymmetric which decompose an image in different ways.This proposal focuses on investigating the use of, and objectively evaluating the different types and families of multiwavelets in the context of stereo correspondence. The end objective of this proposal is to implement a hybrid, multiresolution-based stereo algorithm for video, which takes advantage of the properties exhibited by multiwavelets. An immediate application area of this research would be stereo to 3D (2D+depth) conversion in order to ensure interoperability between the various 3D facilities in our Fused Media Lab. Another equally important objective of this research is to evaluate its possible commercialisation routes in partnership with our industrial collaborators as well as to disseminate and promote the use of multiwavelets in the wider research community.