This paper proposes a new technique based on a non-linear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modelled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighbourhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.
翻译:本文基于非线性 Minmax 检测器( MDB) 过滤器提出了一种新的技术, 其基础是非线性 Minmax 检测器( MDB), 用于图像恢复。 图像升级的目的似乎是从被腐蚀的图像中重建真实图像。 图像获取过程经常导致图像退化, 数字化图像质量低于原始图像。 图像退化可能是由于原始图像中增加了不同类型的噪音。 图像噪音可以模拟多种类型, 脉冲噪音是其中之一。 脉冲噪音产生灰色的像素, 与本地邻居不相符。 它看起来是光和黑暗的, 或只是图像中的光斑点。 过滤是增强图像的一种技术。 线性过滤是一种过滤程序, 输出像素的值是周围值的线性组合, 可能造成图像的模糊性能。 因此, 介质过滤器是最受欢迎的非线性过滤器之一。 当考虑一个小社区时, 它效率很高, 但它是大窗口, 和高噪声会提高图像的清晰度。 过滤器是一种方法, 将图像放大得更模糊化的方法。 。 在中等级的图像中, 降低 水平下, 正在降低 。 。 正在降低 。