How do image statistics impact lossy coding performance?

Author

Saha, Subhasis ; Vemuri, Rao

Author_Institution

California Univ., Davis, CA, USA

fYear

2000

fDate

2000

Firstpage

42

Lastpage

47

Abstract

It has been observed (Saha and Vemuri, 1999) that when we compress a variety of images of different types using a fixed wavelet filter, the peak signal-to-noise ratio (PSNR) values vary widely from image to image. This large variation in PSNR by as much as 30 dB, can only be attributed to the nature and inherent characteristics of the image, since everything else is fixed. In this paper, we analyze the set of test images to determine the features in the images that may cause the coding performance variations. It is shown that most of the gray-level image features do not have any direct effect on the coding performance, and image activity measure is the only feature that has a correlation with the PSNR value

Keywords

data compression; image coding; statistical analysis; transform coding; wavelet transforms; PSNR value; fixed wavelet filter; gray-level image features; image activity measure; image statistics; lossy coding performance; peak signal-to-noise ratio; Biomedical imaging; Filters; Higher order statistics; Histograms; Image analysis; Image coding; PSNR; Performance analysis; Performance loss; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology: Coding and Computing, 2000. Proceedings. International Conference on

Conference_Location

Las Vegas, NV

Print_ISBN

0-7695-0540-6

Type

conf

DOI

10.1109/ITCC.2000.844181

Filename

844181