Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition

Darun Kesrarat; Vorapoj Patanavijit

doi:10.1117/12.2266724

8 February 2017 Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition

Darun Kesrarat, Vorapoj Patanavijit

Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 102251F (2017) https://doi.org/10.1117/12.2266724
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan

Abstract

In optical flow for motion allocation, the efficient result in Motion Vector (MV) is an important issue. Several noisy conditions may cause the unreliable result in optical flow algorithms. We discover that many classical optical flows algorithms perform better result under noisy condition when combined with modern optimized model. This paper introduces effective robust models of optical flow by using Robust high reliability spatial based optical flow algorithms using the adaptive Lorentzian norm influence function in computation on simple spatial temporal optical flows algorithm. Experiment on our proposed models confirm better noise tolerance in optical flow’s MV under noisy condition when they are applied over simple spatial temporal optical flow algorithms as a filtering model in simple frame-to-frame correlation technique. We illustrate the performance of our models by performing an experiment on several typical sequences with differences in movement speed of foreground and background where the experiment sequences are contaminated by the additive white Gaussian noise (AWGN) at different noise decibels (dB). This paper shows very high effectiveness of noise tolerance models that they are indicated by peak signal to noise ratio (PSNR).

Citation Download Citation

Darun Kesrarat and Vorapoj Patanavijit "Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102251F (8 February 2017); https://doi.org/10.1117/12.2266724

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
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Optical flow

Optical filters

Linear filtering

Tolerancing

Digital filtering

Image filtering

Video

Show All Keywords

Keywords/Phrases

Search In:

Publication Years