基于局部标准差和方向微分的模糊方向识别  

Blurred direction identification based on local standard deviation and directional derivation

作　　者：范海菊[1] 张爱丽[1] 冯乃勤[1] 

机构地区：[1]河南师范大学计算机与信息技术学院,河南新乡453007

出　　处：《计算机应用》2011年第9期2506-2508,2517,共4页journal of Computer Applications

基　　金：河南省重点科技攻关项目(102102210180)

摘　　要：针对最小方向微分算法在运动模糊方向识别中误差大和实时性差的缺点,提出利用局部标准差和方向微分相结合的方法鉴定模糊方向。该方法首先对模糊图像进行局部标准差滤波以增强模糊方向上的纹理细节,然后利用双线性插值求最小方向微分和,其对应的方向即为模糊方向;在对方向微分和曲线归纳分析后找到了其内在规律,基于此规律提出范围对半递减搜索最小值的方法,减少了搜索次数。实验结果表明该算法识别精度高,抗干扰性强,实时性好。Concerning the shortcomings of big recognition error and bad real-time calculation by the minimum differential directional algorithm, a method in combination with local standard deviation and directional derivation was put forward to identify the blurred direction of motion blur image. Firstly, the motion blur image was filtered by local standard deviation to enhance texture details in blurred direction. Secondly, the minimum directional derivation summation was obtained by bilinear interpolation, and its corresponding direction was the blurred direction. Meanwhile, the inherent law was found after concluding and analyzing the minimum directional derivation summation curve. Based on this law, the method of search range decreasing in half was presented to search minimum, which could reduce searching times. The simulation results show that this algorithm not only has high orecision and stron~ immunity, but also meets the requirement of real-time calculation.

关 键 词：运动模糊 模糊方向 局部标准差 方向微分 双线性插值 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]