基于小波分频和二次均衡的图像增强算法

传统的图像增强算法在增强图像的同时也增强了图像的噪声信号,导致信息熵下降.结合小波变换多尺度、多分辨率的特点和直方图均衡的优势,提出一种基于小波分频和二次均衡的高亮度图像增强算法.首先利用小波变换将图像分解为低频分量和高频分量,然后仅对低频分量作直方图均衡处理,再由均衡后的低频分量与各高频分量进行小波重构,最后对重构的图像再次进行直方图均衡处理.实验结果表明,该算法对于亮度较高的灰度图像有较好的增强效果.

AN IMAGE ENHANCEMENT ALGORITHM BASED ON WAVELET FREQUENCY DIVISION AND BI-HISTOGRAM EQUALIZATION

The traditional image enhancement algorithms enhance noise signal in image while they enhance image,which leads to the descent of information entropy.With the combination of the characteristics of multi-scale and multi-resolution of wavelet transform and the predominance of histogram equalization,an image enhancement algorithm based on wavelet frequency division and bi-histogram equalization is put forward for images of high brightness.First,the image is divided into the low frequency part and the high frequency parts,and histogram equalization processing is only applied to the low frequency part.Then,the wavelet is reconstituted by the low frequency part which has been equalized and the original high frequency parts.Finally,histogram equalization is applied to the reconstituted image.The experimental results show that this algorithm can enhance images of high brightness effectively.