For the existence of speckle in SAR image, it is very difficult to obtain good segmentation result with traditional methods. In the paper, a new method of SAR image segmentation is proposed with the combination of the features of SAR image and multi-resolution analysis of wavelet. First, texture features are abstracted in wavelet domain. Second, SAR image is filtered according to the feature of its distribution in the wavelet domain. At last, with Fuzzy C-Means clustering technique (FCM), SAR image is segmented according to the vector composed by wavelet texture features and gray level of SAR image filtered. The experiment results show that the new method is efficient in SAR image segmentation.

ABSTRACT:With the development of modern remote sensing technology, a variety of earth observation satellites could continue to tremendously provide image data of different spatial resolution, time resolution, spectral resolution remote sensing, and the remote sensing data obtained is increasing with great capacity, which forms multi-source image pyramid in the same area. To play the advantages of a variety of remote sensing data, the application of remote sensing image fusion is a very important choice. When remote sensing data is large, fusion is large in computing capacity and time-consuming, so it is difficult to carry out rapid, real-time fusion. However, in some remote sensing applications, such as disaster prevention and relief quick, etc., timely fusion is required. Based on image fusion method of principal component analysis (PCA) and the advantage of parallel computing, a high-efficiency fusion method of multi-spectral image and panchromatic image is proposed. Beijing-1 Micro-satellite is a high-performance small satellite for earth observation，With Beijing-1 Micro-satellite remote sensing images as the experimental data, it is proved that good fusion results of multi-spectral image and panchromatic image can be obtained with the proposed method, and the fusion speed is also fast. At the same time, some measures of improving the efficiency of parallel image fusion are also discussed. 1．INTRODUCTIONWith the development of modern remote sensing technology, a variety of earth observation satellites could continue to tremendously provide image data of different spatial resolution, time resolution, spectral resolution remote sensing, and the remote sensing data obtained is increasing with great capacity, which forms multi-source image pyramid in the same area. In such cases, in the description of the same object with multiple-source remote sensing information, how to conduct effective data processing, and play the advantages of a variety of remote sensing data, the application of remote sensing image fusion is a very important choice. When remote sensing data is large, fusion is large in computing capacity and time-consuming, so it is difficult to carry out rapid, real-time fusion. However, in some remote sensing applications, such as disaster monitoring, prevention and relief, dynamic monitoring on plant diseases and insect pests of agriculture, etc., rapid even real-time fusion is required [1][2][3][4][5][6][7].In high-performance computing, parallel cluster computing system has a higher cost-effective ratio and good expansibility, which can meet different large-scale computing problems, and increasing importance has been attached to it. The PCA image fusion method is an important one in image fusion. In the paper, based on the analysis of the process of the PCA image fusion method, and with the advantages of parallel computing, a high-efficiency fusion method of multi-spectral image and panchromatic image is studied and proposed. Beijing-1 Micro-satellite is a high-performance small satellite for earth ob...

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