基于局部复杂度的图像过渡区提取与分割

IMAGE TRANSITION REGION EXTRACTION AND SEGMENTATION BASED ON LOCAL COMPLEXITY

传统的图像过渡区提取算法基于梯度算子,算法对噪声敏感且受剪切值Llow与Lhigh的限制.通过对过渡区像素属性的深入分析,提出基于局部复杂度的过渡区直接提取算法.局部复杂度的滤波作用提高了算法的抗噪性,直接提取则使算法摆脱了对Llow与Lhigh的依赖.实验结果表明,局部复杂度方法优于传统的基于梯度算子的过渡区间接提取方法.

Traditional transition region extraction methods are based on gradient operator. They are sensitive to noise and restricted by Llow and Lhigh. By analyzing properties of transition regions, a novel local complexity based on transition region extraction method （C-TREM） was presented. C-TREM is a direct method to extract transition regions. The filtering ability of local complexity improves the ability of C-TREM to deal with noises. C-TREM depends no more on Llow and Lhigh. Experimental results demonstrate that C-TREM significantly outperforms the conventional gradient-based transition region extraction methods （G-TREM）