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．

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 bedenoted without zigzag,and false corners with zigzag appearance can be effectively suppressed.Then,a competitivesuppression algorithm,which defines a corner similarity with the constraint of neighborhood size according to theDLD response value,and merges similar corners with the WTA strategy,is put forward to remove slowly- varyingcorners.Experimental results show that the typical GLCP detector and the FAST detector combined with DLD areboth 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.