主要工作如下：1。提出了一种基于中值滤波与小波变换的指纹图像去噪方法。
The main contributions are summarized as follows:1. Proposed an integrated denoising algorithm based on mid-value filtering and wavelet transform of fingerprint image.
提出一些在光束描述和传输变换中值得进一步研究的问题，并作了简略分析。
Some problems, which are of interest for further study of the optical beam characterization, propagation and transformation are proposed and briefly analyzed.
通过给出特殊例子说明了对于适中值极性指标序列，该变换不满足灰靶变换的定义。
An observation is constructed to show that it is not suitable for POL(mem) criterion sequence in terms of the definition of grey target transformation.
算法在性能指标和视觉质量上均优于基于离散正交小波变换的阈值去噪方法和传统的中值滤波法。
In performance and visual quality, the algorithm is better than the wavelet denoising based on discrete orthogonal wavelet transform and the conditional median value filtering method.
针对小波变换多分辨分析(mra)的特点，本文提出一种多尺度分级的自适应模糊权重中值滤波的去噪方法。
According to the feature of the MRA, this paper presents a noise filtering method of adaptive fuzzy threshold for wavelet classification base on multi resolution.
将子波包变换和中值滤波相结合，可以有效地降低图像噪声。
Applying median filtering will effectively reduce the impulse noise, which can combine wavelet packet transform and median filter.
通过确当的途径获取缺陷图像，并对图像进行灰度变换，中值滤波对图像进行增强处理，为下一步图像的进一步的处理做前期的准备。
To obtain defect images through appropriate approach and conduct gray-level transformation, and the images are enhancement processed with median filtering, so as to get ready for further processing.
图像的消噪实验表明，小波变换用于图像消噪效果优于均值滤波，与中值滤波去噪相比无明显差别。
Image denoising experiments show that wavelet transform for image denoising is better than mean filtering, no significant difference compared with median filter.
中值滤波，该函数用来对图像进行阈值变换。
Median filter, the function is used to transform the image threshold.
本文研究了金免疫层析试条的智能定量测试系统，着重探讨了中值滤波、小波变换滤波在构建全新的智能金免疫层析试条测试系统中的应用。
The thesis studies the smart quantitative measurement system of immune colloidal-gold strips, specially on the application of median filtering and wavelet in the system.
利用中值滤波和基于小波变换的去噪声处理对同时含有高斯噪声和脉冲噪声的X线图像降噪方法进行探讨。
This paper evaluated median filter in company with wavelet transformation to process X-ray image that contained Gauss noise and impulse noise at the same time.
利用中值滤波和基于小波变换的去噪声处理对同时含有高斯噪声和脉冲噪声的X线图像降噪方法进行探讨。
This paper evaluated median filter in company with wavelet transformation to process X-ray image that contained Gauss noise and impulse noise at the same time.
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