Title :
Image complexity and spatial information
Author :
Honghai Yu ; Winkler, Stefan
Author_Institution :
ECE Dept., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
The complexity of an image tells many aspects of the image content and is an important factor in the selection of source material for testing various image processing methods. We explore objective measures of complexity that are based on compression. We show that spatial information (SI) measures strongly correlate with compression-based complexity measures. Among the commonly used SI measures, the mean of the edge magnitude is shown to be the best predictor. Moreover, we find that compression-based complexity of an image normally increases with decreasing resolution.
Keywords :
data compression; image coding; SI measures; compression-based complexity; edge magnitude; image complexity; image content; image processing methods; objective measures; source material selection; spatial information; Complexity theory; Correlation; Image coding; Image resolution; Integrated circuits; Silicon; Transform coding; Image quality; Kolmogorov complexity; SI; image compression; resolution;
Conference_Titel :
Quality of Multimedia Experience (QoMEX), 2013 Fifth International Workshop on
Conference_Location :
Klagenfurt am Wo??rthersee
DOI :
10.1109/QoMEX.2013.6603194
