Paper Info
Title
A new fast matching method for adaptive compression of stereoscopic images
Abstract
In the last few years, due to the growing use of stereoscopic images, much effort has been spent by the scientific community to develop algorithms for stereoscopic image compression. Stereo images represent the same scene from two different views, and therefore they typically contain a high degree of redundancy. It is then possible to implement some compression strategies devoted to exploit the intrinsic characteristics of the two involved images that are typically embedded in a MPO (Multi Picture Object) data format. MPO files represents a stereoscopic image by building a list of JPEG images. Our previous work introduced a simple block-matching approach to compute local residual useful to reconstruct during the decoding phase, stereoscopic images that maintain high perceptual quality; this allows to the encoder to force high level of compression at least for one of the two involved images. On the other hand the matching approach, based only on the similarity of the blocks, results rather inefficient. Starting from this point, the main contribution of this paper focuses on the improvement of both matching step effectiveness and its computational cost. Such alternative approach aims to greatly enhance matching step by exploiting the geometric properties of a pair of stereoscopic images. In this way we significantly reduce the complexity of the method without affecting results in terms of quality.
Year
DOI
Venue
2015
10.1117/12.2086372
Proceedings of SPIE
Keywords
Field
DocType
Stereoscopic Images,Image Compression,Multi Picture Object,Epipolar Geometry
Computer vision,Residual,Computer science,Stereoscopy,Exploit,JPEG,Redundancy (engineering),Encoder,Artificial intelligence,Decoding methods,Image compression
Conference
Volume
ISSN
Citations 
9393
0277-786X
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
alessandro ortis1248.54
Sebastiano Battiato237441.37