Artificial vision systems cannot process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. Inspired by biological perception systems, artificial attention models pursuit to select only the relevant part of the scene. On human vision, it is also well established that these units of attention are not me...

[22] A. Sha'ashua and S. Ullman, Structural saliency: the detection of globally salient structures using a locally connected network, curves ending abruptly. Since all computations are performed on a discrete grid, quantization and rounding errors restrict the selectivity and amount of clutter the system can handle. It is possible to base much of the reasoning of the voting and interpretation o...

Full-reference image quality assessment (FR-IQA) techniques compare a reference and a distorted/test image and predict the perceptual quality of the test image in terms of a scalar value representing an objective score. The evaluation of FR-IQA techniques is carried out by comparing the objective scores from the techniques with the subjective scores (obtained from human observers) provided in t...

Saliency map generation in synthetic aperture radar (SAR) imagery has become a promising research area, since it has a close relationship with quick potential target identification, rescue services, etc. Due to the multiplicative speckle noise and complex backscattering in SAR imagery, producing satisfying results is still challenging. This paper proposes a new saliency map generation approach ...

The localization of spatially extended objects is thought to be based on the computation of a default reference position, such as the center of gravity. This position can serve as the goal point for a saccade, a locus for fixation, or the reference for perceptual localization. We compared perceptual and saccadic localization for non-convex shapes where the center of gravity (COG) was located ou...

In this paper, we present a video saliency detection method by spatio-temporal sampling and sparse matrix decomposition. In the method, we sample the input video sequence into three planes: X-T slice plane, YT slice plane, and X-Y slice plane. Then, motion saliency map is extracted from the X-T and Y-T slices, and static saliency map is extracted from the X-Y slices by low-rank matrix decomposi...

This paper presents a novel method for detecting saliency in static images based on image sparse representation. For each color channel, first, the image is partitioned into non-overlapping patches and each patch is represented by the way of sparse coding from a learned dictionary of patches from natural scenes. Then, global saliency and local saliency are calculated and fused to attain salienc...

generally human vision system searches for salient regions and movements in video scenes to lessen the search space and effort. using visual saliency map for modelling gives important information for understanding in many applications. in this paper we present a simple method with low computation load using visual saliency map for background subtraction in video stream. the proposed technique i...

To aim at the defect that the classic significant region detection algorithm IG suppresses the most significant pixels, a novel saliency detection method combined with neighborhood inhomogeneity factor NIF is put forward. This algorithm achieves the satisfying result in static image saliency detection. Firstly, IG saliency map is obtained according to the IG algorithm, and then the NIF saliency...

Salient region detection is important for many high-level computer vision tasks. The majority of previous works exploit element contrast to detect image saliency region. In this paper, we propose a novel approach to analyze saliency cues from multiple scales of image structure, using a multi-scale image abstraction. In each image layer global color contrast cue and color spatial distribution cu...