中文摘要：

目的 针对目前已有的纹理平滑方法难以在抑制强梯度和尺度变化纹理的同时保持完整结构的问题，提出一种结构识别引导下的纹理抑制图像平滑算法。方法 首先，结构与纹理的根本区别在于重复模式，结构应该是稀疏的，而纹理应该是一个有重复模式的区域，因此，通过对结构/纹理的多尺度分析，提取了对于结构/纹理具有辨别力的多尺度内变差特征；然后，借助支持向量机，对提取的特征样本点训练出一个结构/纹理分类器；就分类结果中存在的结构较粗、毛刺等问题，进一步对分类结果进行细化和剔除毛刺与孤立点的后处理操作，以获得最终的更为精细的结构识别结果；最后，提出结构引导下的自适应双边图像滤波算法，达到既能抑制强梯度和尺度变化的纹理又能保持结构完整性的图像平滑效果。结果 本文提出的多尺度内变差特征在支持向量机训练中达到了96.12%的正确率，结构引导下的图像滤波能够在保持结构的同时，有效地抑制强梯度和尺度变化的纹理细节。结论 本文算法在兼顾结构的保持和强梯度以及尺度变化纹理的抑制方面超越了已有的方法，对于结构提取、细节增强、图像分割、色调映射、图像融合和目标识别等众多技术领域的发展将具有较强的促进作用，体现了潜在的实际应用价值。

英文摘要：

Objective Natural scenes generally contain different scale objects and textures,which carry rich information in regard to human perception.Texture usually signifies pixel values,which change with high frequency.Generally,images are composed of many important structures,texture,edges,etc.Therefore,mining the meaningful structure from textures or complex background images is a critical task in vision processing.The core of image smoothing lies in the separation of structure and texture.Effective preservation of the structure while suppressing the texture with strong gradient or varying scales is a challenging problem.Most of the existing image smoothing methods tends to deal with weak gradient texture images;if the texture gradient is strong,then these methods will fail.To solve the abovementioned problem,a structure recognition guided texture smoothing algorithm is proposed,which deals with the structure and the texture separately and detect structure before image smoothing.Method First,this paper argues that the fundamental difference between structure and texture is the repetition pattern.Particularly,the structure should be sparse and the texture should be a region with a repeating pattern.According to this characteristic,the discriminative features for distinguishing between structure and texture are designed and extracted based on the multi-scale analysis of inherent variation.At least two reasons are available for presenting the multi-scale approach.One reason is that structure and texture are relative.When the scale is small,the texture may not show up,and thus the scale needs to be enlarged and the essence of the texture is released.The other reason is that the texture in the image is diverse,and the adaptive scale in different regions is difficult.Furthermore,textures with various attributes may exist in the same image,a single scale can only solve the partial texture with the default scale parameter and the recognition of other textures will lose.Therefore,multi-scale analysis of inherent variation is pr