2026-04-17T03:55:22Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/4679882026-03-28T08:38:11Zcom_2072_98col_2072_378192

00925njm 22002777a 4500 dc Murray, Naila author Vanrell i Martorell, Maria Isabel author Otazu Porter, Xavier author Parraga, Carlos Alejandro author 2013 We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics. Computational models of vision Color Hierarchical image representation Low-level spatiochromatic grouping for saliency estimation