基于数学形态学的混合图像均值滤波方法研究
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摘要
以往采用多方向滤波、中值滤波、F.Safa滤波对混合图像进行滤波处理,存在效果差的问题,为了改善混合图像质量,提出了基于数学形态学的均值滤波方法。根据混合图像结构元素选取流程,分析不同混合图像结构元素尺寸,当元素尺寸被选定后,结合均值滤波原理,分析最大结构元素尺寸变化内的各种形态,在去除噪声同时保留完整图像边缘。依据形态学均值滤波处理过程,引入数学形态学中开闭运算方法,根据开闭运算步骤,计算像素值与原像素差值,获取噪声像素点,进行形态学计算,在保留原有信号前提下,对混合图像进行除燥处理,由此完成混合图像均值滤波方法研究。通过实验对比结果可知,该方法最高除燥效果可达到95%,为混合图像更加清晰展示提供支持。
In the past,multi-direction filtering,median filtering and F. Safa filtering were used to filter mixed images,which had poor effect. In order to improve the quality of mixed images,a mean filtering method based on mathematical morphology was proposed. According to the process of selecting structural elements of mixed images,the sizes of different structural elements of mixed images are analyzed. When the sizes of elements are selected,combined with the principle of mean filtering,the various shapes within the change of the maximum size of structural elements are analyzed,and the noise is removed while preserving the complete image edges. According to the process of morphological mean filtering,the open-close operation method in mathematical morphology is introduced. According to the step of openclose operation,the difference between the pixel value and the original pixel value is calculated,the noise pixel point is obtained,and the morphological calculation is carried out. On the premise of retaining the original signal,the mixed image is dehumidified,thus the mixed image mean value is completed. Filtering method. The experimental results show that the maximum drying effect of this method can reach 95%,which provides support for clearer display of mixed images.
In the past,multi-direction filtering,median filtering and F. Safa filtering were used to filter mixed images,which had poor effect. In order to improve the quality of mixed images,a mean filtering method based on mathematical morphology was proposed. According to the process of selecting structural elements of mixed images,the sizes of different structural elements of mixed images are analyzed. When the sizes of elements are selected,combined with the principle of mean filtering,the various shapes within the change of the maximum size of structural elements are analyzed,and the noise is removed while preserving the complete image edges. According to the process of morphological mean filtering,the open-close operation method in mathematical morphology is introduced. According to the step of openclose operation,the difference between the pixel value and the original pixel value is calculated,the noise pixel point is obtained,and the morphological calculation is carried out. On the premise of retaining the original signal,the mixed image is dehumidified,thus the mixed image mean value is completed. Filtering method. The experimental results show that the maximum drying effect of this method can reach 95%,which provides support for clearer display of mixed images.
引文
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[2]李明,李梦萄,邓光平,等.基于CMOS图像传感器混合噪声的自适应滤波算法[J].半导体光电,2016,37(4):568-572.
[3]王凡,彭国华,谢昊伶.基于形态学增强和图像融合的板带钢缺陷检测[J].激光与红外,2018,16(1):124-128.
[4]惠振阳,胡友健.基于LiDAR数字高程模型构建的数学形态学滤波方法综述[J].激光与光电子学进展,2016,15(8):1-7.
[5]吴延海,张婧,陈康.改进的基于均值滤波的单幅图像去雾算法研究[J].西安科技大学学报,2016,36(4):583-588.
[6]宫鹏涵,周克栋,赫雷,等.形态滤波方法在抵肩力信号降噪中的应用研究[J].兵工学报,2017,38(7):1416-1421.
[7]钟国舜,钟四成,李明,等.基于图像传感器的图像画质增强算法研究[J].半导体光电,2017,38(4):580-584.
[8]刘剑,李彤,孙睿,等.基于混合滤波算法的太阳光斑图像位置跟踪[J].沈阳工业大学学报,2017,39(4):438-443.
[9]徐蕾,彭月平,贺科宁.基于改进双边滤波与随机共振的图像去噪算法研究[J].激光杂志,2018,15(8):43.
[10]宋清昆,马丽,曹建坤,等.基于小波变换和均值滤波的图像去噪[J].黑龙江大学自然科学学报,2016,12(4):555-560.
[11]公茂法,蔡芬,刘秀杰,等.基于数学形态学和改进Prony算法的谐波与间谐波参数估计[J].电测与仪表,2018,55(11):25-26.
[12]张兰花,贾振红,杨杰,等.基于Tetrolet与数学形态学相结合的遥感图像增强[J].激光杂志,2018,14(2):48-52.
[13]李凯,张烨.基于Matlab直方图技术的图像增强方法研究[J].自动化与仪器仪表,2017,18(10):45-48.
[14]王秋云.一种改进的照度不均图像增强方法[J].自动化与仪器仪表,2017,32(2):33-35.
[15]李雅楠.基于灰度融合的彩色图像渐变设计[J].电子设计工程,2018(20):165-168.
[16]庄玉册,赵莉苹.关于运动图像模糊区域边界优化降噪仿真[J].计算机仿真,2018,35(5):322-325.
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