硕士论文-FIN1feng

1、西北工业大学硕士学位论文 摘要I摘 要遥感图像分割是遥感图像分析和解译中的关键技术之一，对有效利用遥感数据，进一步进行信息提取与目标识别等工作具有重要意义。高分辨率遥感图像包含丰富的颜色、纹理等信息，图像本身也含有大量噪声，因此如何较好地移除噪声，并合理利用图像所包含的各类信息对图像进行准确分割是高分辨率遥感图像分割研究中的一个经典问题。算法是一种可依次实现图像滤波、颜色量化和空间分割的彩色图像分JSEG割方法，但该方法直接用于遥感图像分割时，往往由于遥感图像中区域边界较模糊而导致对区域边界分割不准确，或由于区域内不同阴影而出现过分割现象。为了有效实现对区域边界的准确分割，本文利用能更好描述区域内颜色的同质性的局部同质矩阵校正传统 JSEG 算法中的局部值，以实现对区域边界的准确反映，J提高区域边界分割的准确性。为了减弱或消除传统算法的过分割现象，本JSEG文利用能稳定描述图像纹理特征的算子进行具有相似纹理信息的颜色类/LBP C图的合并。最后，采用分析法、优度实验法中的评价测度，在算法中值JSEGJ和均值计算的基础上给出了值和均值评价方法，对本文方法的分割效果进JJJ行评价。仿真实验

2、结论表明本文提出的改进算法可有效克服传统的算法在JSEGJSEG高分辨遥感图像分割时存在的边界分割不准确及过分割现象。关键词: 高分辨率遥感图像，算法，局部同质，算子JSEG/LBP C西北工业大学硕士学位论文 AbstractIIAbstract（重新翻译）In order to effectively analyze and interpret the remote sensing data, the remote sensing image processing technology has become hotspot. The remote sensing image segmentation is one of key factors, which decide the success of remote sensing image analyze and calculation. Because only if the better segmentation effect is obtained, the follow-up works can be get better

3、 effects, such as information extraction and target recognition et al. The background of this paper is high resolution remote sensing image. As these remote sensing images contain a wealth of color, texture and a lot of noise et al, the key point of the research is how to effectively remove noise, smooth the image and reasonably use various information to segment the image. Firstly, the image filtering, color space quantization and spatial segmentation can be completely simultaneously by use the

4、 JSEG algorithm, which directly utilize color information. Then, In order to solve the limitation case of the JSEG, such as over segmentation, the improved JSEG algorithm is proposed in this paper. For obtaining the better effect of segmentation, the local J value is corrected by local homogeneous matrix, which gives reasonably description for color homogeneity in region and the boundary of different region. In addition, for weakening or eliminating the over segmentation, the class map is merged

5、 by LBP/C operator. It gives stable description for the texture of image. The finally, the evaluation of image segmentation is analyzed and summarized. In addition, the evaluation method of J value and J average value is proposed based on calculating the J value and J average value in JSEG algorithm. The merit is reflected by objective evaluation data. The experiment results show that the high resolution color remote sensing image is effectively segmented by the JSEG algorithm and improved JSEG

6、algorithm. In addition, the shortages of JSEG is effectively overcome by the improved method, for example, the over segmentation and inaccurate location of region boundary.Key words: High resolution color remote sensing image, JSEG algorithm, Local homogeneity, LBP/C operator西北工业大学硕士学位论文 目录III目 录摘 要.IAbstract.II目 录.III第一章 绪论Equation Chapter 1 Section 1.11.1课题研究背景及意义.11.1.1 遥感图像成像与处理.11.1.2 遥感图像处理研究意义.21.2遥感图像分割发展现状.31.2.1 图像分割技术发展现状.31.2.2 高分辨率遥感图像分割发展现状.41.3论文主要工作及内容.7第二章 基于 JSEG 算法的彩色遥感图像分割Equation Chapter 2 Section 1.92.1彩色特征空间.102.2JSEG 算法 .112.2.1 彩色图像的颜色量化.112.2.2 空间分割算法.192.3JSEG 算法分割彩色遥感图像实验 .262.3.1 分割实验.262.3.2 实验结果及分析.272.4本章小结.

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