文档介绍：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,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行评价。
仿真实验结论表明本文提出的改进算法可有效克服传统的算法在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
Abstract(重新翻译)
In order to effectively analyze and interpret the remote sensing data, the remote sensing image processing technology has e hotspot. The remote sensing image segmentation is one of key factors, which decide the ess of remote sensing image analyze and calculation. Because only if the better segmentation effect is obtained, the follow-up works can be get better 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 pletely simultaneously by use the 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 by LBP/C operator. It gives stable description for the texture of image. The finally, th