Dynamic adjustment of regularization parameters for the fusion of edge features and noisy dense surfaces

C. Richardson; Renato A. Salinas Silva; Mongi A. Abidi

doi:10.1117/12.220946

15 September 1995 Dynamic adjustment of regularization parameters for the fusion of edge features and noisy dense surfaces

C. Richardson, Renato A. Salinas Silva, Mongi A. Abidi

Author Affiliations +

Proceedings Volume 2589, Sensor Fusion and Networked Robotics VIII; (1995) https://doi.org/10.1117/12.220946
Event: Photonics East '95, 1995, Philadelphia, PA, United States

Abstract

Data fusion provides tools for solving problems which are characterized by distributed and diverse information sources. Many robotic applications need to retrieve particular properties from a scene; so it is necessary to use multiple knowledge sources since a single sensory modality cannot capture all of the physical causes of a given edge feature. In this paper we focus on the problem of extracting features such as image discontinuities from both synthetic and real images. Since edge detection and surface reconstruction are ill-posed problems according to Hadamard, Tikhonov's regularization paradigm is proposed as the basic tool for solving this inversion problem and restoring well-posedness. The proposed framework includes (1) a review of 2D regularization, (2) extension of the standard Tikhonov regularization method by allowing space-variant regularization parameters, and (3) further extension of the regularization paradigm by adding multiple data sources for different sensing modalities. The theoretical approach is complemented by developing a regularized hybrid fusion algorithm for solving the early vision problems of edge detection and surface reconstruction. An evaluation of these methods reveals that this new analytical data fusion technique reconstructs a smooth filtered surface in noisy regions while preserving edge characteristics needed for extracting object features. Results indicate the fusion technique is beneficial for combining edge features from different types of sensory data to locate and identify objects of interest.

Citation Download Citation

C. Richardson, Renato A. Salinas Silva, and Mongi A. Abidi "Dynamic adjustment of regularization parameters for the fusion of edge features and noisy dense surfaces", Proc. SPIE 2589, Sensor Fusion and Networked Robotics VIII, (15 September 1995); https://doi.org/10.1117/12.220946

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
12 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Sensors

Data fusion

Edge detection

Image fusion

Fusion energy

Algorithm development

Image segmentation

Show All Keywords

Keywords/Phrases

Search In:

Publication Years