Boundary Detection Using Double-Opponency and Spatial Sparseness Constraint
Boundary Detection Using Double-Opponency and Spatial Sparseness Constraint
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使用双对抗和空间稀疏约束的边界检测
DOI：
10.1109/tip.2015.2425538
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发表时间：
2015-08-01
影响因子：
10.6
通讯作者：
Li, Yong-Jie
中科院分区：
文献类型：
--
作者：
Yang, Kai-Fu;Gao, Shao-Bing;Li, Yong-Jie
亮度和色彩是人类视觉系统（HVS）为更好地理解色彩自然场景而整合的两个基本视觉特征。为了将这两种线索结合起来，最大限度地提高自然场景边界检测的可靠性，我们提出了一种基于HVS初级视觉皮层（V1）中某类颜色敏感双对手（DO）细胞的颜色对手机制的新框架。这种类型的DO细胞具有定向的接受野，具有色彩和空间上的对立结构。提出的框架是一个前馈层次模型，与视网膜到V1的颜色对抗机制有直接对应关系。此外，我们利用神经响应的空间稀疏性约束（SSC）进一步抑制纹理元素的无用边缘。实验结果表明，当DO细胞的锥体输入不平衡时，所建立的DO细胞可以灵活地捕获复杂场景中显著目标的结构色差边界和消色差边界。同时，SSC算子通过抑制冗余纹理边缘进一步提高了性能。该模型具有具有竞争力的轮廓检测精度，而且实现简单，计算成本低。
Brightness and color are two basic visual features integrated by the human visual system (HVS) to gain a better understanding of color natural scenes. Aiming to combine these two cues to maximize the reliability of boundary detection in natural scenes, we propose a new framework based on the color-opponent mechanisms of a certain type of color-sensitive double-opponent (DO) cells in the primary visual cortex (V1) of HVS. This type of DO cells has oriented receptive field with both chromatically and spatially opponent structure. The proposed framework is a feedforward hierarchical model, which has direct counterpart to the color-opponent mechanisms involved in from the retina to V1. In addition, we employ the spatial sparseness constraint (SSC) of neural responses to further suppress the unwanted edges of texture elements. Experimental results show that the DO cells we modeled can flexibly capture both the structured chromatic and achromatic boundaries of salient objects in complex scenes when the cone inputs to DO cells are unbalanced. Meanwhile, the SSC operator further improves the performance by suppressing redundant texture edges. With competitive contour detection accuracy, the proposed model has the additional advantage of quite simple implementation with low computational cost.