Image sequence coding using data classification

Gang Tu; Luc Van Eycken; Andre J. Oosterlinck

doi:10.1117/12.23526

1 November 1990 Image sequence coding using data classification

Gang Tu, Luc Van Eycken, Andre J. Oosterlinck

Proceedings Volume 1349, Applications of Digital Image Processing XIII; (1990) https://doi.org/10.1117/12.23526
Event: 34th Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1990, San Diego, CA, United States

Abstract

In this paper a specific data classification approach is presented which can be used in coders for transmitting video sequences. The image data is locally classified into four categories prior to the coding process which is then divided in four modes in order to exploit the masking effect of motion and to reach high performance. The four categories are: moving area containing an edge (data class Cf) moving area containing no single edge (class C/j) still area containing an edge (class C) and still area containing no single edge (class CE). This classification approach is based on the fact that the human visual system is especially sensitive to edge information and this in function of the motion behavior. Generally it is known that the edge information is critical to the human eyes. In the moving areas however the human eyes are less critical of the spatial details in comparison to that in the still areas because of the masking effect of motion. The data in the moving areas can be treated relatively coarsely but when edges are observed the quality criterion should still be raised appropriately. Using this four-mode coding method the subjective reproduction quality can be improved even in the case of low bit-rate applications. This classification approach is applied in the conventional motion compensating hybrid (DCT/DPCM) coder although it can also be with other coders.

Citation Download Citation

Gang Tu, Luc Van Eycken, and Andre J. Oosterlinck "Image sequence coding using data classification", Proc. SPIE 1349, Applications of Digital Image Processing XIII, (1 November 1990); https://doi.org/10.1117/12.23526

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