@Article{iasc.2020.010117,
AUTHOR = {Lei Feng, Haibin Li, Yakun Gao, Yakun Zhang},
TITLE = {The Application of Sparse Reconstruction Algorithm for Improving  Background Dictionary in Visual Saliency Detection},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {26},
YEAR = {2020},
NUMBER = {4},
PAGES = {831--839},
URL = {http://www.techscience.com/iasc/v26n4/40287},
ISSN = {2326-005X},
ABSTRACT = {In the paper, we apply the sparse reconstruction algorithm of improved 
background dictionary to saliency detection. Firstly, after super-pixel 
segmentation, two bottom features are extracted: the color information of LAB 
and the texture features of the image by Gabor filter. Secondly, the convex hull 
theory is used to remove object region in boundary region, and K-means 
clustering algorithm is used to continue to simplify the background dictionary. 
Finally, the saliency map is obtained by calculating the reconstruction error. 
Compared with the mainstream algorithms, the accuracy and efficiency of this 
algorithm are better than those of other algorithms.},
DOI = {10.32604/iasc.2020.010117}
}