通常的红外含噪图像增强方法很难有效滤除图像中噪声。提出一种新的红外含噪图像自适应增强算法以克服边缘增强和抑制噪声的矛盾。首先采用尖锐频率局部化Contourlet变换完成图像分解;然后采用分层自适应阈值算法估计降噪阈值,并进行自适应降噪;最后对降噪后高频带通信号引入图像清晰度参数,设计半软阈值增强函数,实现红外含噪图像自适应增强。实验结果验证了新方法的有效性。

The enhanced infrared noisy image usually involves noise which is difficult to be eliminated by traditional methods. A new adaptiveenhancing algorithm for infrared noisy image was proposed to overcome the contradiction of enhancing edge and suppressing noise. Firstly, the decomposition of noisy image was accomplished by using a new Contourlet transform with sharp frequency localization. Then, the coefficients were denoising in different scale and direction according to the shrinkage thresholds, which were estimated with layering adaptivethreshold algorithm. Finally, an image sharpness metric, which was used to calculate semi-soft threshold enhancement function, was applied to the denois high frequency sub-band images. Thus, the local pixels of noisy image were adaptively enhanced. Experimental results show that the proposed algorithm is effective.