一种基于不规则区域的高斯滤波去噪算法

针对传统高斯滤波算法在滤除噪声的同时会丢失图像部分细节信息的弊端,提出了一种基于不规则区域的高斯滤波算法。在高斯滤波的基础上,通过分析纹理自相关特性,自适应构造局部不规则的高斯掩模窗口,突破以往采用固定大小窗口的思想,提高高斯系数权值分配的合理性,剔除相关性较低的像素,实现在滤波的同时有效保留图像纹理细节。实验结果表明,提出的算法优于传统高斯滤波及其他滤波算法,在图像细节保留和抗噪方面实现了较好的平衡。

Improved Denoising Algorithm Based on Non-regular Area Gaussian Filtering

Because traditional Gaussian filter often blurs the edge structure in images,an improved Gaussian filtering algorithm based on non-regular area was proposed in the paper.The algorithm based on Gaussian filtering breaks traditional thought of adopting fixed window,adaptively constructs non-regular Gaussian mask region through analyzing the self-similarity of texture.The rationality of weighted values distributed by Gaussian function is further improved to maintain rich texture as the potential noise or lower similar pixels are rejected in non-regular areas.Experimental results show that the proposed algorithm makes a better balance between enhancing image details and denoising,and is better than traditional Gaussian filtering and other methods.