基于小波变换和中值滤波的FMI信号去噪方法

介绍了二维离散小波变换下的图像分解与重构算法。在图像分解与重构的基础上，提出应用中值滤波和二雏离散小波变换相结合的方法对舍噪的FMI图像进行去噪处理，通过实例验证，采用新方法对一口溶蚀孔洞储层井的FMI图像进行去噪分析，并与单一的中值滤波或小波变换法的结果进行比较。实验结果表明，应用二维小波分析结合传统方法对FMI图像进行去噪，能够有效地去除图像中的随机噪声，其结果优于单一的中值滤波或小渡分析法，对提高油、气层裂缝和孔洞的自动识别具有重要的指导意义。

FMI SIGNAL DE-NOISING BASED ON WAVELET TRANSFORM AND MEDIAN FILTERING

The algorithm of wavelet decomposition and reconstruction was introduced. Based on the decomposition and reconstruction of image, the application of the traditional median filtering method and two-dimensional discrete wavelet transform to noise elimination was analyzed. A corresponding example of application was given. In the example, the new method was applied in one FMI image from a cavernous reservoir, and the resultant image was compared with the single usage in de-noising image. The results showed that the random noise was eliminated and the automatic identification of fractures and caverns were enhanced effectively by preprocessing using FMI images with two-dimensional discrete wavelet transform combined with traditional methods, and the combination was much better than single usage of these two methods.