中文摘要：

为了去除图像锯齿边缘的伪角点，减少平滑缓变角点的重复检出，提出了多向格型微分（DLD）算子，结合“胜者全取”（WTA）的竞争抑制策略，改善角点检测的性能．首先，针对锯齿失真，提出一种基于Directionlet分解的微分算子，其多向格型复合表示能实现任意方向图像边缘的无锯齿结构分解，很好地抑制锯齿特征的伪角点现象．其次，针对缓变角点，提出竞争响应抑制法，它根据DLD响应值定义一个以邻域尺寸为约束条件的角点相似度，相似角点通过WTA策略合并。实验结果表明，联合DLD的GLCP检测器和FAST检测器能分别使误检和漏检综合评价指标ACU值提高12．14％和6．32％，改善效果明显．

英文摘要：

A multi-direction latticed differential （DLD）operator combined with the “Winner Takes All （WTA）”competitive suppression strategy is proposed to remove the false corners along zigzag image edges and the repeatedly-detected corners in smooth regions,which improves the performance of the corner detector.In the investigation, first,a differential operator based on the Directionlet decomposition is proposed to eliminate the zigzag distortion. With the multi-direction latticed complex representation of the operator,image edges in arbitrary direction can be denoted without zigzag,and false corners with zigzag appearance can be effectively suppressed.Then,a competitive suppression algorithm,which defines a corner similarity with the constraint of neighborhood size according to the DLD response value,and merges similar corners with the WTA strategy,is put forward to remove slowly-varying corners.Experimental results show that the typical GLCP detector and the FAST detector combined with DLD are both obviously improved.For instance,the ACU value,which is a comprehensive evaluation index of the error de-tection rate and the missed detection rate,increases by 12.14% and 6.32%,respectively.