| 1. | Speckle noise suppression and filtering methods for spaceborne sar images
图像的斑点噪声抑制与滤波研究 |
| 2. | Speckle in sar images will affect the precision of recognition , should be removed before classing
Sar图像的斑点噪声对识别率影响较大，在目标识别前需把斑点从图像中去除掉。 |
| 3. | In chapter 1 we particularly research the mechanism of speckle coming into being and the statistical characteristic of sar image
第一章着重研究了斑点噪声的形成机理及sar图像的统计特性。 |
| 4. | Both filtering methods can significantly reduce speckle noise , and at the same time preserve the image notable details
两种算法都可以在滤除斑点噪声的同时较好地保留图像的突出细节特征。 |
| 5. | In this paper , a nonlinear multiwavelet transform adaptive threshold value method is proposed to suppress speckle noise
摘要文章提出了一种新的用于斑点噪声抑制的非线性多小波变换自适应阈值算法。 |
| 6. | The arising mechanism , model and statistical characteristics of speckle noise are described and the popular filters are analyzed
首先介绍了斑点噪声产生机理、模型和统计特征，对常用的图像滤波器进行了分析。 |
| 7. | In chapter 3 traditional algorithms of suppressing speckle are discussed . the main parameters for evaluating the quality of image are introduced
第三章分析了常见的斑点噪声抑制算法，介绍了主要的图像质量评估指标。 |
| 8. | Based on the above two points , algorithms research in speckle suppression and multi - source image fusion were chosen as the main topic in this paper
本文针对以上两个方面，对sar图像斑点噪声去除和多源遥感数据融合算法进行了研究。 |
| 9. | In chapter 2 we particularly describe the mechanism of speckle forming , discuss the noise model and the statistical characteristic of sar image
第二章首先讨论了斑点噪声的形成机理，研究了斑点噪声模型，然后分析了sar图像的统计特性。 |
| 10. | The result of the method is better than the traditional one . the segment filter method has been proposed also , whose result is better than filters directly
本文还提出了先进行图像分割再滤波的方法,它的滤波效果比直接进行斑点噪声滤波的效果要好。 |
