基于局部复杂度的图像过渡区提取与分割

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Lbigh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Lbigh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．

IMAGE TRANSITION REGION EXTRACTION AND SEGMENTATION BASED ON LOCAL COMPLEXITY

Traditional transition region extraction methods are based on gradient operator. They are sensitive to noise and restricted by L_(low) and L_(high) . 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 L_(eow) and L_(high). Experimental results demonstrate that C-TREM significantly outperforms the conventional gradient-based transition region extraction methods (G-TREM)