基于二进小波变换的噪声图像自适应增强新算法

针对图像增强算法通常会放大原图像中噪声分量的问题,提出了一种基于二进小波变换的图像增强新算法。该算法充分利用了二进小波变换的平移不变性和各尺度上小波系数间的相关性,有效改善了增强过程中噪声放大和边缘失真问题。此外,算法具有高度的自适应能力,适用性更强。实验结果表明,与目前已有的各类多尺度图像增强算法相比,该算法在抑制噪声和凸显图像特征两方面均有明显改进。

An Adaptive Strategy for Image Enhancement Based on the Dyadic Wavelet Transform

A new algorithm for image enhancement based on the dyadic wavelet transform is proposed aiming at minimizing the image noise while amplifying the image feature. By making full use of the shift invariability of the dyadic wavelet transform and correlation of the wavelets coefficients from different scales, the proposed algorithm can efficiently alleviate the amplification of the noise and distortion of edges, which are the most difficult and common problems in image enhancement. Furthermore, the enhancing strategy is highly adaptive and thus applicable to images from many sources. The results of experiments are also given, which show that the new algorithm performs better in both de noising and image feature enhancing compared with the existing multi scale algorithms.