基于去噪阈值的图像平滑模糊算法方法研究

提出了一种高效的基于模糊概念的平滑算法，它采用加权平均来取代传统的均值操作，并引入了相邻度概念，把相邻度设为像素的权值，还采用点对块处理来取代传统的点对点处理，同时利用去噪阈值来取代传统的分割阈值，因而使得用此方法处理过的图像更加清晰，尤其在噪声较多且复杂的情况下，它的优势就更明显．实验表明，该方法比基于传统平滑算法的去噪效果有较大提高。

Research for image smoothing fuzzy approaches based on removed-noise threshold

An efficient smoothing algorithm is presented based on fuzzy class. The weight average instead of traditional average operation and the conception of neighborhood were introduced, which was assigned as weight value. This algorithm also advanced pixelblock operation instead of pixel-pixel operation and removed-noise threshold instead of segmentation threshold, which caused the image more explicit and showed obvious superiority especially when the noise is more complex. Results show that the approach based on fuzzy smoothing approach provides a more powerful noise removal~ ability than the classical ones.