IEEE Trans Image Process. 2015 Aug;24(8):2565-78. doi: 10.1109/TIP.2015.2425538. Epub 2015 Apr 22.
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.
亮度和颜色是人类视觉系统（HVS）集成的两个基本视觉特征，以更好地理解颜色自然场景。为了结合这两个线索，最大限度地提高自然场景中边界检测的可靠性，我们提出了一种基于 HVS 初级视觉皮层（V1）中某种类型的颜色对手型双拮抗（DO）细胞的颜色对手机制的新框架。这种类型的 DO 细胞具有带色和空间拮抗结构的定向感受野。所提出的框架是一个前馈分层模型，与从视网膜到 V1 涉及的颜色对手机制直接对应。此外，我们利用神经反应的空间稀疏性约束（SSC）进一步抑制纹理元素的不需要的边缘。实验结果表明，当 DO 细胞的锥细胞输入不平衡时，我们建模的 DO 细胞可以灵活地捕捉复杂场景中显著物体的结构化颜色和非颜色边界。同时，SSC 算子通过抑制冗余纹理边缘进一步提高了性能。具有竞争性轮廓检测精度，所提出的模型具有额外的优势，即具有较低的计算成本和相当简单的实现。
