A robust algorithm for compression and reconstruction of infrared thermal image sequence

Jin-Yu Zhang; Yong-Chao Ma; Sheng-Jie Tao; Yin Li

doi:10.1117/12.2244463

29 August 2016 A robust algorithm for compression and reconstruction of infrared thermal image sequence

Jin-Yu Zhang, Yong-Chao Ma, Sheng-Jie Tao, Yin Li

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100333E (2016) https://doi.org/10.1117/12.2244463
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

Quickly and accurately processing and saving high resolution thermal image sequences is a key technique in the field of thermal wave nondestructive testing. Based on the theory of thermal wave attenuation, this paper proposed a simple, fast and anti-noise global compression and reconstruction algorithm and showed the ability to improve the reliability and speed. Firstly the new algorithm divides the thermal image spatially and classifies thermal sequence. Then each curve in different temperature drop periods was fitted and lastly the compression and reconstruction of thermal sequence is fulfilled simultaneously in space and time by using the typical classified curve parameters as the compression and reconstruction parameters of thermal sequence. To verify the effect of the new algorithm, the experiment and comparison were carried out. The results show that the algorithm is a rapid, accurate and reliable. Compared with the current fitting compression method, it not only has a strong compression and anti-noise ability but also improve the operation speed up to hundreds of thousands of times.

Citation Download Citation

Jin-Yu Zhang, Yong-Chao Ma, Sheng-Jie Tao, and Yin Li "A robust algorithm for compression and reconstruction of infrared thermal image sequence", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100333E (29 August 2016); https://doi.org/10.1117/12.2244463

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