Visualizing Natural Image Statistics

被引：5

作者：

Fang, Hui ^{[1
]}

Tam, Gary Kwok-Leung ^{[1
]}

Borgo, Rita ^{[1
]}

Aubrey, Andrew J. ^{[2
]}

Grant, Philip W. ^{[1
]}

Rosin, Paul L. ^{[2
]}

Wallraven, Christian ^{[3
]}

Cunningham, Douglas ^{[4
]}

Marshall, David ^{[2
]}

Chen, Min ^{[5
]}

机构：

[1] Swansea Univ, Dept Comp Sci, Swansea SA2 8PP, W Glam, Wales

[2] Cardiff Univ, Dept Comp Sci, Cardiff CF10 3AT, S Glam, Wales

[3] Korea Univ, Dept Brain & Cognit Engn, Seoul, South Korea

[4] Brandenburg Tech Univ Cottbus, Brandenburg, Germany

[5] Univ Oxford, Oxford E Res Ctr, Oxford OX1 3QG, England

来源：

IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS | 2013年 / 19卷 / 07期

基金：

英国工程与自然科学研究理事会;

关键词：

Image statistics; image visualization; usability study; visual design; COMPONENT ANALYSIS; COLOR TRANSFER;

D O I：

10.1109/TVCG.2012.312

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Natural image statistics is an important area of research in cognitive sciences and computer vision. Visualization of statistical results can help identify clusters and anomalies as well as analyze deviation, distribution, and correlation. Furthermore, they can provide visual abstractions and symbolism for categorized data. In this paper, we begin our study of visualization of image statistics by considering visual representations of power spectra, which are commonly used to visualize different categories of images. We show that they convey a limited amount of statistical information about image categories and their support for analytical tasks is ineffective. We then introduce several new visual representations, which convey different or more information about image statistics. We apply ANOVA to the image statistics to help select statistically more meaningful measurements in our design process. A task-based user evaluation was carried out to compare the new visual representations with the conventional power spectra plots. Based on the results of the evaluation, we made further improvement of visualizations by introducing composite visual representations of image statistics.

引用

页码：1228 / 1241

页数：14

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