An image similarity measure using homogeneity regions and structure

Eric P. Lam; Kenny C. Loo

doi:10.1117/12.767493

28 January 2008 An image similarity measure using homogeneity regions and structure

Eric P. Lam, Kenny C. Loo

Proceedings Volume 6808, Image Quality and System Performance V; 680811 (2008) https://doi.org/10.1117/12.767493
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

There are many uses of an image quality measure. It is often used to evaluate the effectiveness of an image processing algorithm, yet there is no one widely used objective measure. It can be used to compare similarity between two-dimensional data. In many papers, the mean squared error (MSE) or peak signal to noise ratio (PSNR) are used. These measures rely on pixel intensities instead of image structure. Though these measures are well understood and easy to implement, they do not correlate well with perceived image quality. This paper will present an image quality metric that analyzes image structure rather than entirely on pixels. It extracts image structure with the use of quadtree decomposition. A similarity comparison function based on contrast, luminance, and structure will be presented.

Citation Download Citation

Eric P. Lam and Kenny C. Loo "An image similarity measure using homogeneity regions and structure", Proc. SPIE 6808, Image Quality and System Performance V, 680811 (28 January 2008); https://doi.org/10.1117/12.767493

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