基于改进三维块匹配滤波的红外全息降噪算法北大核心CSCD

红外全息技术更适用于长距离的大视场成像,但其散斑噪声与高斯噪声对图像质量的影响也更加显著,限制了红外全息技术的应用与推广。本文通过引入全局傅立叶阈值与自适应维纳滤波的方法对三维块匹配滤波算法进行优化,提高了其对红外全息图像降噪的适应性与细节保留,得到改进的三维块匹配滤波算法,并与多种采用传统滤波方法的结果进行了对比。结果表明,改进后的算法可以在对红外全息图像中的高斯噪声等环境噪声与散斑噪声进行降噪的同时保留更多细节,是一种更加适用于红外全息图像的降噪方法。

Infrared holographic noise reduction algorithm based on improved three dimensional block matching filtering

Infrared holographic technology is particularly suitable for long distance,large field of view imaging,but its susceptibility to speckle noise and Gaussian noise significantly affects image quality,limiting its application and promotion.In this paper,the 3D block matching filter algorithm is optimized by introducing global Fourier thresholding and adaptive Wiener filtering methods to improve its adaptability and detail preservation in denoising infrared holographic images.The improved 3D block matching filter algorithm is obtained and compared with the results obtained using various traditional filtering methods.The results show that the improved algorithm can effectively reduce Gaussian noise and speckle noise in infrared holographic images while preserving more details,and is more suitable denoising method for infrared holographic images.