Double-Line Multi-scale Fusion Pedestrian Saliency Detection

2018 ◽  
pp. 144-154
Author(s):  
Jiaxuan Zhuo ◽  
Jianhuang Lai
Keyword(s):  
Saliency Detection ◽  
Double Line ◽  
Multi Scale

Multi-scale Image Partitioning and Saliency Detection for Single Image Blind Deblurring

2021 ◽  
pp. 508-523
Author(s):  
Jiaqian Yan ◽  
Yu Shi ◽  
Xia Hua ◽  
Zhigao Huang ◽  
Ruzhou Li
Keyword(s):  
Saliency Detection ◽  
Single Image ◽  
Multi Scale ◽  
Blind Deblurring

scholarly journals A Multi-Scale Colour and Keypoint Density-Based Approach for Visual Saliency Detection

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 121330-121343
Author(s):  
Alessandro Bruno ◽  
Francesco Gugliuzza ◽  
Roberto Pirrone ◽  
Edoardo Ardizzone
Keyword(s):  
Saliency Detection ◽  
Visual Saliency ◽  
Multi Scale ◽  
Visual Saliency Detection

scholarly journals Echoic log-surprise: A multi-scale scheme for acoustic saliency detection

2018 ◽  
Vol 114 ◽  
pp. 255-266 ◽  
Author(s):  
Antonio Rodríguez-Hidalgo ◽  
Carmen Peláez-Moreno ◽  
Ascensión Gallardo-Antolín
Keyword(s):  
Saliency Detection ◽  
Multi Scale ◽  
Scale Scheme

scholarly journals Research on an Infrared Multi-Target Saliency Detection Algorithm under Sky Background Conditions

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 459
Author(s):  
Shaosheng Dai ◽  
Dongyang Li
Keyword(s):  
Saliency Detection ◽  
Infrared Image ◽  
Detection Algorithm ◽  
Saliency Map ◽  
Phase Spectrum ◽  
Background Suppression ◽  
Suppression Effect ◽  
Multi Scale ◽  
Saliency Maps ◽  
Image Saliency

Aiming at solving the problem of incomplete saliency detection and unclear boundaries in infrared multi-target images with different target sizes and low signal-to-noise ratio under sky background conditions, this paper proposes a saliency detection method for multiple targets based on multi-saliency detection. The multiple target areas of the infrared image are mainly bright and the background areas are dark. Combining with the multi-scale top hat (Top-hat) transformation, the image is firstly corroded and expanded to extract the subtraction of light and shade parts and reconstruct the image to reduce the interference of sky blurred background noise. Then the image obtained by a multi-scale Top-hat transformation is transformed from the time domain to the frequency domain, and the spectral residuals and phase spectrum are extracted directly to obtain two kinds of image saliency maps by multi-scale Gauss filtering reconstruction, respectively. On the other hand, the quaternion features are extracted directly to transform the phase spectrum, and then the phase spectrum is reconstructed to obtain one kind of image saliency map by the Gauss filtering. Finally, the above three saliency maps are fused to complete the saliency detection of infrared images. The test results show that after the experimental analysis of infrared video photographs and the comparative analysis of Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) index, the infrared image saliency map generated by this method has clear target details and good background suppression effect, and the AUC index performance is good, reaching over 99%. It effectively improves the multi-target saliency detection effect of the infrared image under the sky background and is beneficial to subsequent detection and tracking of image targets.

scholarly journals Multi-scale Feature Fusion for 3D Saliency Detection

2020 ◽  
Vol 1651 ◽  
pp. 012128
Author(s):  
Gang Pan ◽  
An-Zhi Wang ◽  
Bao-Lei Xu ◽  
Weihua Ou
Keyword(s):  
Feature Fusion ◽  
Saliency Detection ◽  
Scale Feature ◽  
Multi Scale
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