基于图像增强的改进自适应加权均值滤波算法

为了尽可能滤除图像中的椒盐噪声同时改善图像视觉效果，将改进自适应加权均值滤波与小波域图像增强技术有机结合，提出了一种具有增强效果的图像滤波算法。该算法分为滤波和滤波后处理两个阶段。滤波阶段，对经典均值滤波分别从噪声检测策略、权值计算机方法噪声滤波模版设计等方面进行适当改进，给出了具体实现步骤；滤波后处理阶段，首先将滤波后图像进行三层小波分解；然后构造出一种小波图像增强模型，根据小波系数的幅度值将其分为三个部分，分别进行不同程度的拉伸处理；最后进行拉伸后小波系数重构。将该滤波算法与经典均值滤波，加权均值滤波、自适应加权中值滤波等性能比较，实验结果表明，本文滤波算法在噪声滤除和图像细节保持方面，效果较好。

A improved adaptive weighted average filtering algorithm based on digital image enhancement

In order to filter out the salt & pepper noise in digital image and improve visual effect at the same time,combining with the improved adaptive weighted average filter and the technique of wavelet domain image enhancement,a new image filtering algorithm based image enhancement is put forward.The filtering algorithm is divided into two steps of filtering and post-processing.At the filtering stage,the classical average filtering is improved in the noise detection strategy,the methods of the weight values computing and design new filter templates.Then,the concrete implementation steps is given.At the stage of filtering post-processing,Firstly,the filtering image is conducted three layers wavelet transform.Secondly,a new enhancement model of wavelet domain is structured.According to the amplitude value of the wavelet coefficients,the filtering image is divied into three parts.They are tensile processed in different degree respectively.Finally,the wavelet coefficients is reconstructed.The experiment show that the performance of the filtering algorithm is better than the classical average filtering algorithm,adaptive weighted average filtering algorithm and adaptive weighted median filtering algorithm.