Visual Conspicuity Index: Spatial Dissimilarity, Distance, and Central Bias

Visual Conspicuity Index: Spatial Dissimilarity, Distance, and Central Bias
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DOI:
10.1109/lsp.2011.2167752
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发表时间:
2011-09
影响因子:
3.9
通讯作者:
Lijuan Duan;C. Wu;Jun Miao;A. Bovik
Lijuan Duan;C. Wu;Jun Miao;A. Bovik
中科院分区:
工程技术2区
文献类型:
--
作者:
Lijuan Duan;C. Wu;Jun Miao;A. Bovik

文献摘要

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We propose an image conspicuity index that combines three factors: spatial dissimilarity, spatial distance and central bias. The dissimilarity between image patches is evaluated in a reduced dimensional principal component space and is inversely weighted by the spatial separations between patches. An additional weighting mechanism is deployed that reflects the bias of human fixations towards the image center. The method is tested on three public image datasets and a video clip to evaluate its performance. The experimental results indicate highly competitive performance despite the simple definition of the proposed index. The conspicuity maps generated are more consistent with human fixations than prior state-of-the-art models when tested on color image datasets. This is demonstrated using both receiver operator characteristics (ROC) analysis and the Kullback-Leibler distance metric. The method should prove useful for such diverse image processing tasks as quality assessment, segmentation, search, or compression. The high performance and relative simplicity of the conspicuity index relative to other much more complex models suggests that it may find wide usage.