The increasing evidence that language processing is sensitive to lexical and structural co-occurrences at different levels of granularity and abstraction (Jurafsky, Bell, Gregory, & Raymond, 2001; Bybee, 2006) has led to the hypothesis that lexical and structural processing may be unified (MacDonald, Pearlmutter, & Seidenberg, 1994; Jurafsky, 1996). This paper examines the specific hypothesis t...

Starting instead from a symmetric-antisymmetric reformulation we first show SSIM to be a contrast or visibility function in the classic sense. Furthermore, the previously enigmatic structural covariance is revealed to be the difference of variances. The second step, eliminating the intrinsic quadratic nature of SSIM, allows a near linear correlation with human observer scores, and without invok...

A method has been developed for the evaluation of spectral library search methods to measure their capability in giving useful results if the unknown is not contained in the database. The similarities of the chemical structures in the hitlist and the structure of a test compound are measured by the Tanimoto index (calculated for a set of binary substructure descriptors). Results for IR and MS d...

The Structural Similarity (SSIM) Index is a very widely used image/video quality model that continues to play an important role in the perceptual evaluation of compression algorithms, encoding recipes and numerous other processing algorithms. Several public implementations SSIM Multiscale-SSIM (MS-SSIM) algorithms have been developed, which differ efficiency performance. This "bendable ruler" m...

Sparse coding theory demonstrates that the neurons in primary visual cortex form a sparse representation of natural scenes in the viewpoint of statistics. In this paper, we propose a novel sparse coding model based on structural similarity for natural image patch feature extraction. The advantage for our model is to be able to preserve structural information from a scene, which human visual per...