基于小波分解和异步重构的图像信息增强算法

摘要

针对传统基于小波变化的图像信息增强问题,提出了一种结合小波分解和异步重构的图像信息增强算法.其中的异步重构方法并不采用通常的顺序,而是采用排序编码来执行.通过模拟人脑处理视觉信息的方式,该方法试图通过使用较少的频率通道来实现图像重构.首先,信号首先通过高斯差分滤波实现空间频率分解.然后选择最重要信息频率分量,每个像素利用最好的尺度进行重构,并且忽略弱响应尺度.实验结果表明:在局部重构的情况下,相比传统的标准排序重构算法,提出的算法能够快速的实现图像重建并达到较高的增强效果.%Aiming at the problem of image information enhancement based on wavelet transform,an image infor-mation enhancement algorithm based on wavelet decomposition and asynchronous reconstruction was proposed. The asynchronous reconstruction method does not use the usual order,but uses the sort code to carry out. By sim-ulating human brain processing visual information,this method attempted to achieve image reconstruction by using fewer frequency channels. Firstly,the signal is firstly decomposed by Gauss difference filter. Then the most im-portant information frequency component was selected,and each pixel was reconstructed with the best scale,and the weak response scale was ignored. Experimental results show that,as compared with the traditional standard sorting reconstruction algorithm,the proposed algorithm could achieve fast image reconstruction and achieve high enhancement performance in the case of partial reconstruction.