Point filtering used as a texture magnification or minification filter.
用作纹理放大或缩小筛选器的点筛选。
In order to more effectively make use of local features to restore the noise-infected image, a nonlinear filtering algorithm based on local texture direction probability statistic model was proposed.
为了更有效地利用图像的局部特征恢复被噪声感染的图像，基于图像局部纹理方向概率统计模型，提出一种针对混合噪声的非线性滤波算法。
The algorithm first executed the adaptive morphological filtering of fusion to restrain dark noise and texture details of the images.
该算法对图像进行多结构多尺度自适应形态滤波处理，从而抑制图像的暗噪声和暗纹理细节。
In principle, this allows us to apply any standard texture recognition algorithm for the task (e. g., the multi-channel Gabor filtering technique).
原则上，我们可以采用任意一种标准的纹理识别算法(例如：多通道伽柏滤波器方法)。
As part of the final scene pass, the bloom texture is scaled to the size of the back buffer using bilinear filtering and added directly to the output of the scene.
作为最终场景的一部分，光晕纹理缩小到使用双线性过滤和场景直接输出的后缓冲尺寸。
Then normal filtering and texture environment operations are performed using the texture image.
然后，对纹理图象施加滤波和纹理环境操作。
Much of other useful information about texture properties such as texture orientations and scales are lost during the diffusion filtering.
为了充分利用纹理结构的其他信息，如方向特性、尺度特性等，论文又将该方法扩展到矢量形式。
It helps the texture look much smoother than filtering alone when it is minified.
在缩小纹理时，它会比单独的过滤更平滑。
It helps the texture look much smoother than filtering alone when it is minified.
在缩小纹理时，它会比单独的过滤更平滑。
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