Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Compressive Stereo Cameras for Computing Disparity Maps

Not Accessible

Your library or personal account may give you access


Compressive imaging employs the direct measurement of object features and has been shown to offer both performance (e.g., improved reconstructed image fidelity) and cost (e.g., reduced number of measurements relative to the native dimensionality) advantages. We examine compressive imaging within a stereo vision application in which a traditional correspondence algorithm is used to find pixel disparity maps. Through simulation we show that compressive imaging provides sufficient image fidelity with 12.8× compression to compute disparity maps with less that 4.5% error on average at 0.5% relative measurement noise strength.

© 2013 Optical Society of America

PDF Article
More Like This
Computer-generated holograms using stereo disparity with a multi-matching algorithm

Yan-Ling Piao, Ki-Chul Kwon, Jeong-Hyeon Lee, Sang-Keun Gil, and Nam Kim
27P_101 Conference on Lasers and Electro-Optics/Pacific Rim (CLEO/PR) 2015

Self-organizing neural network for computing stereo disparity and transparency

Jonathan A. Marshall
FDD6 OSA Annual Meeting (FIO) 1990

Recovering view and world geometry from stereo disparities

Richard P. Wildes
FN1 OSA Annual Meeting (FIO) 1988

Select as filters

Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved