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Multiwavelet Evaluation for Stereo Correspondence

立体对应的多小波评估

基本信息

批准号：
EP/G029423/1
负责人：
Cristian Serdean
金额：
$ 24.62万
依托单位：
De Montfort University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2009
资助国家：
英国
起止时间：
2009 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FG029423%2F1
关键词：
Multiwavelet Evaluation Stereo Correspondence

项目摘要

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.

立体视觉是从立体图像中提取深度信息的过程，其离散形式具有多种实际应用，从娱乐，广播，3D建模和可视化到机器人和自动化工业检测，仅举几例。计算左右立体图像之间的视差-也称为立体对应匹配-是立体视觉应用中最具挑战性的阶段。在生物学上，人类大脑通过采用多通道、多分辨率机制来实现这一任务，认识到自然视觉场景包含多个分辨率的细节信息。离散立体视觉可以在空间域和频率域中进行。空间图像处理技术在空间上提供了完美的定位，但在频率上没有定位。传统的图像变换在频率上实现了完美的定位，但没有（或非常差）空间定位。Wavelet是第一个提供分层多分辨率方法的现代变换，它结合了两个世界的优点：原始图像的空间频率分层多分辨率分解，具有局部和全局空间支持（第2.3节）。它们迅速成为立体声通信的流行选择。为了在立体对应的上下文中实现最佳性能，小波应该理想地同时具有以下属性：正交性，局部性（即紧支持，平滑滤波器和大量消失矩）和对称性。不幸的是，小波不可能同时拥有所有这些特征。幸运的是，这不是多小波的情况下，一个相对较新的，多通道的（标量）小波的竞争对手。尽管应用型多小波是一个相当缺乏研究的课题，但在许多应用中，它们已经被证明比标量小波表现得更好。此外，有不同类型的多小波可用：可分离与不可分离，平衡与不平衡，双对称与双对称反对称，分解图像以不同的方式。本建议侧重于调查的使用，并客观地评估不同类型和家庭的多小波立体对应的上下文中。该建议的最终目标是实现一个混合的，基于多分辨率的立体视频算法，它利用多小波所表现出的属性。这项研究的一个直接应用领域是立体到3D（2D+深度）的转换，以确保我们融合媒体实验室中各种3D设备之间的互操作性。这项研究的另一个同样重要的目标是与我们的工业合作伙伴合作评估其可能的商业化路线，以及在更广泛的研究界传播和推广多小波的使用。