[期刊论文]


Saliency detection based on aggregated Wasserstein distance

作   者:
Fengdong Sun;Wenhui Li;

出版年:2018

页    码:1 - 1
出版社:SPIE-Intl Soc Optical Eng


摘   要:

This paper proposes a saliency detection method based on the aggregated Wasserstein distance. A multidimensional Gaussian mixture model is used to model the superpixels, whereby the color information of different color spaces is combined. To overcome the lack of the closed-form solution for the Gaussian mixture model, we employ the aggregated Wasserstein distance to measure the perceptual similarity between different superpixels. The saliency value is then calculated from two aspects. First, the global saliency is computed through all the superpixels in the image using the aggregated Wasserstein distance. Second, the local saliency is computed in a lower range with the same measure. Finally, a saliency map is obtained by combining the two types of saliencies, and is filtered by spectral clustering all the superpixels. The experimental results show that the proposed method outperforms 11 recent exact algorithms on three widely used open datasets.



关键字:

RGB color model ; Image segmentation ; Lithium ; 3D modeling ; Image processing ; Optical filters ; Visualization ; Visual process modeling ; Distance measurement ; Fourier transforms


所属期刊
Journal of Electronic Imaging
ISSN: 1017-9909
来自:SPIE-Intl Soc Optical Eng