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Multiresolution based hierarchical disparity estimation for stereo image pair compression

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TLDR
A multiresolution based approach is proposed for compressing 'still' stereo image pairs and the typical computational gains and compression ratios possible with this approach are provided.
Abstract
Stereo vision is the process of viewing two different perspective projections of the same real world scene and perceiving the depth that was present in the original scene. These projections offer a compact 2-dimensional means of representing a 3-dimensional scene, as seen by one observer. Different display schemes have been developed to ensure that each eye sees the image that is intended for it. Each image in the image pair is referred to as the left or right image depending on the eye it is intended for. The binocular cues contain unambiguous information in contrast to monocular cues like shading or coloring. Hence binocular stereo may be quite useful, for instance, in video based training of personnel. On the entertainment side, it can make mundane TV material lively. Though the concept has been around for more than half a century, only recently have technically effective ways of making stereoscopic displays and the usually required eyeware emerged. Despite this progress, stereo TV can be made a cost effective add-on option only if the increased bandwidth requirement is relaxed somehow. Since the two images are projections of the same scene from two nearby points of view, they are bound to have a lot of redundancy between them. By properly exploiting this redundancy, the two image streams might be compressed and transmitted through a single monocular channel's bandwidth. The first step towards stereoscopic image sequence compression is 'still' stereo image pair compression that exploits the high correlation between the left and right images, in addition to exploiting the spatial correlation within each image. The temporal correlation between the frames can be taken advantage of, along the lines of the MPEG (Motion Picture Experts Group) standards, to achieve further compression. The final step would be to explore the correlation between left and right frames with a time offset between them. In this paper a multiresolution based approach is proposed for compressing 'still' stereo image pairs. In Section II the task at hand is contrasted with the stereo disparity estimation problem in the machine vision community; a block based scheme on the lines of a motion estimation scheme is suggested as a possible approach. In Section III, the suitability of hierarchical techniques for disparity estimation is outlined. Section IV provides an overview of wavelet decomposition. Section V details the multiresolution approach taken. In section VI, the typical computational gains and compression ratios possible with this …

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Citations
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Proceedings ArticleDOI

A wavelet based stereo image coding algorithm

TL;DR: A wavelet based stereo image pair coding algorithm is proposed that is efficient to achieve stereo image compression and improves the accuracy of estimation of wavelet images produced by the disparity compensation technique.
Proceedings ArticleDOI

Multiresolutional region-based segmentation scheme for stereoscopic image compression

TL;DR: In this article, a disparity-based segmentation approach is proposed to achieve an efficient partition of the image into regions of more or less fixed disparity, in order to minimize the edge artifacts after disparity compensation.
Patent

Method of time-efficient stereo matching

TL;DR: In this paper, a time efficient stereo matching method which is applicable at an algorithm level is presented, which is compatible with and thus can be employed to any types of stereo matching implementation.
Journal ArticleDOI

Stereo video coding based on quad-tree decomposition of B– P frames by motion and disparity interpolation

TL;DR: In this paper, an improved interpolated motion and disparity estimation (EIMDE) method was proposed to encode the frames of the right image sequence by exploiting both the temporal redundancy of the same sequence and the disparity redundancy with the left image sequence.
Journal ArticleDOI

A least-squares-based 2-D filtering scheme for stereo image compression

TL;DR: A two-dimensional (2-D) least squares (LS)-based filtering scheme for high fidelity stereo image compression applications is introduced in this correspondence and the results were benchmarked against those of the block-matching method.
References
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A theory for multiresolution signal decomposition: the wavelet representation

TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
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Orthonormal bases of compactly supported wavelets

TL;DR: This work construct orthonormal bases of compactly supported wavelets, with arbitrarily high regularity, by reviewing the concept of multiresolution analysis as well as several algorithms in vision decomposition and reconstruction.
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The Laplacian Pyramid as a Compact Image Code

TL;DR: A technique for image encoding in which local operators of many scales but identical shape serve as the basis functions, which tends to enhance salient image features and is well suited for many image analysis tasks as well as for image compression.
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Multiresolution image processing and analysis

TL;DR: A Hierarchical Image Analysis System Based Upon Oriented Zero Crossings of Bandpassed Images and a Tutorial on Quadtree Research.
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