Perceptually-based Comparison of Image Similarity Metrics


Autoria(s): Russell, Richard; Sinha, Pawan
Data(s)

20/10/2004

20/10/2004

01/07/2001

Resumo

The image comparison operation ??sessing how well one image matches another ??rms a critical component of many image analysis systems and models of human visual processing. Two norms used commonly for this purpose are L1 and L2, which are specific instances of the Minkowski metric. However, there is often not a principled reason for selecting one norm over the other. One way to address this problem is by examining whether one metric better captures the perceptual notion of image similarity than the other. With this goal, we examined perceptual preferences for images retrieved on the basis of the L1 versus the L2 norm. These images were either small fragments without recognizable content, or larger patterns with recognizable content created via vector quantization. In both conditions the subjects showed a consistent preference for images matched using the L1 metric. These results suggest that, in the domain of natural images of the kind we have used, the L1 metric may better capture human notions of image similarity.

Formato

13 p.

9714300 bytes

2612761 bytes

application/postscript

application/pdf

Identificador

AIM-2001-014

CBCL-201

http://hdl.handle.net/1721.1/7235

Idioma(s)

en_US

Relação

AIM-2001-014

CBCL-201

Palavras-Chave #AI #Image matching #vector quantization #Minkowski metric