基于软门限去噪的图象压缩编码研究

在详细地分析了Donoho提出的子波域软限去噪方法的基础上，给出了含噪图象信号噪声水平的估计及门限值随尺度变化的规律。采用可分离的二维子波滤波器，方便地将Donoho的软门限去噪方法应用于图象信号处理，从而对含噪图象，在去除噪声的同时，又最大限度地进行了压缩。针对含噪的自然景物图象和合成孔径雷达图象的不同特点，分别提出了这在图象的压缩方案。对于SAR图象的压缩编码，通过一个自然对数变换，使得乘性噪声转变为适于软门限去噪的加性噪声。模拟结果显示，用软门限方法处理的解压缩图象比硬门限方法具有更好的视觉质量，因而该方法是解决含噪图象压缩编码的有效技术。

Noise Image Coding Using Soft-Threshold Based Denoising

The soft threshold method proposed by Donoho is studied in this paper. The noise standard deviation of noise image and the thresholds of different scale are given. A separable 2 D wavelet filter is used so that the soft threshold denoising by Donoho is expediently applied to image processing, such as simultaneous denosing makes compression rate of a noisy image be large farthest. For noise image of nature scene and SAR, different image compression schemes are proposed respectively. Especially for SAR image, a natural logarithm transfors multiplicative noise to additive noise so that SAR image can be suppressed via the soft threshold denoising scheme. Experimental results show the decoded images by the soft threshold denoising have better quality than by the hard threshold denoising. It indicates that the improved ways in this paper are effective for noise image compression.