一种小波域的图像增强算法

微弱图像具有对比度低、噪声高、质量差等特点,一定程度上影响了图像的观察和使用。因此,提出一种小波域的图像增强算法,通过对微弱图像多尺度、多分辨率的小波变换分离各维度小波系数,对低频小波系数进行直方图均衡化,高频小波系数进行Canny算法提取边缘,最后将处理后的各维度小波系数进行图像重构以实现图像增强。并选取了3幅微弱图像,将其经所提出的算法及几种传统经典图像增强算法增强后的图像进行实验仿真对比。仿真结果表明,在主观评价上,所提算法增强后的图像的细节更加丰富,视觉感受更加平滑自然;客观评价指标中信息熵的值也都是最大的,分别是4.989 3,3.741 5,4.796 1,信息丰富度最高;而峰值信噪比和图像质量测量函数的数据表明所提算法增强图像的强度适中,整体性较好。可见,所提出的针对微弱图像的增强算法能够在视觉效果上和图像信息上进行有效的图像增强。

An Image Enhancement Algorithm Based on Wavelet Domain

Weak image has characteristics such as low contrast, high noise and poor quality, which affected image observation and application to certain degree. Therefore a weak image enhancement algorithm in wavelet domain was proposed through separating the dimensions of the wavelet coefficients by using multi scale and multi resolution wavelet transform from weak image, histogram equalization of low frequency wavelet coefficients, and edge extraction of wavelet coefficients by using Canny operator. Finally, the image enhancement was realized through reconstructing image by combining each dimension of wavelet coefficients. Three pieces of weak images were selected and compared with the traditional image enhancement algorithm. The simulation results showed that three pieces of weak image through this algorithm showed more details in the subjective evaluation, while the visual feeling smoother and more natural. The information entropy of objective evaluation index of value was also the biggest among several classic image enhancement algorithms with the information entropy values being 4.989 3, 3.741 5, 4.796 1 respectively. The PSNR and CE data showed that the proposed algorithm was moderate with the better overall performance. Therefore, enhancement algorithm aimed at weak image was a relatively good image enhancement algorithm, and it achived the effective image enhancement in the visual effect and image information.