图像去噪中的纹理保护方法研究

基于偏微分方程及变分极值最小化的图像平滑方法可以有效地去除噪声，而且能够保护边缘信息，但由于噪声及纹理难以区分，使得纹理信息无法保留。提出一种纹理保护滤波算法，该算法利用图像分解模型将图像分解为几何结构分量及噪声/纹理分量，计算后者的局部方差，与传统变分能量最小化方法中的偏差惩罚项结合形成随纹理变化的约束，得到的模型在纹理区域滤波减少，从而保护了纹理信息。实验在视觉效果上得到了预期的结果，信噪比的计算对比也可以证明算法的有效性。

Studies on Texture Preserving Image Denoising Methods

Image smoothing algorithms based on PDE and variational formulation minimization can denoise effectively while preserving the edge information, but the texture information can not be kept as the noise and texture are difficult to discriminate. A new texture preserving filter is proposed. The new algorithm first uses image decomposition model to separate image into the geometry part and the noise/texture part, then calculates the local variance of the latter which is incorporated with the traditional deviation cost to form a spatially adaptive constraint. The new filter smoothes less in the texture regions, thus could preserve the texture information. The visual effect and data analysis of the experiment result proves the effectiveness of the algorithm.