This method is insensitive to spatial image noise and is in better correspondence with the response of the human visual system than is the standard technique.
这种方法对空间图像噪声不敏感，并且与标准技术相比，它能够更好的与人类视觉系统的反应相一致。
Without considering the spatial information of images, the original fuzzy C-means algorithm is very sensitive to image noise.
由于原始的模糊c -均值聚类算法没有考虑图像的空间信息，算法对图像中的噪音点十分敏感。
The commonly spatial adaptive noise filter can reduce the noise effectively, but at the same time leads to the loss of a large number of image edge detail information.
常用的空间自适应滤波方法在滤除噪声的同时，损失了图像中的大量边缘细节信息。
A method of spatial overlap-add is utilized in this algorithm. It can reduce the block noise exist in the traditional DCT watermarking algorithm and improve the quality of the image.
通过空间交迭的方法，该算法能够削弱传统DCT自适应水印算法的块状噪声，从而提高图像的品质。
These scales represent the process of successive simplification of an image. This means spatial details such as texture and noise are gradually removed, while major edges are maintained.
这些连续的级代表了图像逐渐简化的过程，即更多的细节例如纹理和噪声被逐渐移除，同时主要边缘得以保留。
To improve the Signal-to-noise Ratio(SNR) and detecting probability of small target in infrared image sequences, a novel method of target detection based on spatial-temporal filtering is proposed.
为了提高红外图像序列中弱小目标的信噪比和检测概率，同时考虑检测算法实时性，提出了一种新的基于空时域滤波的小目标检测方法。
The traditional way is to obtain the sub-image by sampling the noised image in spatial or frequency domain, then calculate its variance to replace that of the original noise.
传统方法是通过空域或频域采样，得到该子噪声图像，然后直接对其估计方差，它对图像信息的分布有要求。
The traditional way is to obtain the sub-image by sampling the noised image in spatial or frequency domain, then calculate its variance to replace that of the original noise.
传统方法是通过空域或频域采样，得到该子噪声图像，然后直接对其估计方差，它对图像信息的分布有要求。
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