基于极值检测的图像滤波算法

An Image Filtering Algorithm Based on Extremum Detection

针对极值中值滤波法在去除椒盐噪声时存在的不足,提出了一种改进的图像滤波算法。首先使用极值法检测图像中的噪声点,然后采用窗口由小到大变化的自适应算法得到噪声像素的滤波值,最后通过计算噪声像素滤波前后灰度值的差值来修正被误判像素的灰度值。对不同类型、受不同强度噪声污染图像的去噪实验表明,该方法在不同噪声率下均优于传统的中值滤波法及其一些改进算法,当噪声率较大时其去噪和保边性能得到了显著提高。

Aiming at the shortcoming of extremum median filter in denoising the salt and pepper noise, an improved image filtering algorithm is proposed. The extremum method is used to detect the noise pixel firstly, and then an adaptive multi-window method is adopted to get the filtering value of pixels that is labeled as noise. The modification process is introduced for the wrong-checked pixels by comparing their gray value before and after the filtering. The proposed method is proved to be superior to the traditional median filter and some improved algorithm for the different noise image. The performance of the method is saliently improved in eliminating the noise and preserving the edge of the image when the noise ratio is high