电子科技大学学报
電子科技大學學報
전자과기대학학보
JOURNAL OF UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA
2014年
1期
42-48
,共7页
各向异性高斯窗%非局部均值%SAR图像降斑%Stein无偏风险估计
各嚮異性高斯窗%非跼部均值%SAR圖像降斑%Stein無偏風險估計
각향이성고사창%비국부균치%SAR도상강반%Stein무편풍험고계
anisotropic Gaussian window%non-local means%SAR image despecking%Stein unbiased risk estimation
针对传统空域非局部平均方法在合成孔径雷达图像相干斑抑制中存在相似区域提取和方向信息捕获不足的问题,提出了一种基于各向异性高斯方向窗和Stein’s无偏风险估计(SURE)准则融合的非局部均值(NLM)算法。该方法设计多个不同方向的各向异性高斯窗来匹配SAR图像的局部空间几何结构,比传统的方形窗能更好地保护SAR图像中的方向性结构。采用比率测度来衡量图像块间的相似程度,并计算基于该各向异性高斯窗的NLM结果。结合SURE准则来融合不同方向的各向异性高斯窗的非局部平均结果,获得最终的SAR图像降斑结果。针对多幅SAR图像进行对比实验,实验结果表明:该方法在有效抑制SAR图像相干斑的同时能很好地保留图像的几何结构信息,为后续的SAR图像理解与解译提供了良好的基础。
針對傳統空域非跼部平均方法在閤成孔徑雷達圖像相榦斑抑製中存在相似區域提取和方嚮信息捕穫不足的問題,提齣瞭一種基于各嚮異性高斯方嚮窗和Stein’s無偏風險估計(SURE)準則融閤的非跼部均值(NLM)算法。該方法設計多箇不同方嚮的各嚮異性高斯窗來匹配SAR圖像的跼部空間幾何結構,比傳統的方形窗能更好地保護SAR圖像中的方嚮性結構。採用比率測度來衡量圖像塊間的相似程度,併計算基于該各嚮異性高斯窗的NLM結果。結閤SURE準則來融閤不同方嚮的各嚮異性高斯窗的非跼部平均結果,穫得最終的SAR圖像降斑結果。針對多幅SAR圖像進行對比實驗,實驗結果錶明:該方法在有效抑製SAR圖像相榦斑的同時能很好地保留圖像的幾何結構信息,為後續的SAR圖像理解與解譯提供瞭良好的基礎。
침대전통공역비국부평균방법재합성공경뢰체도상상간반억제중존재상사구역제취화방향신식포획불족적문제,제출료일충기우각향이성고사방향창화Stein’s무편풍험고계(SURE)준칙융합적비국부균치(NLM)산법。해방법설계다개불동방향적각향이성고사창래필배SAR도상적국부공간궤하결구,비전통적방형창능경호지보호SAR도상중적방향성결구。채용비솔측도래형량도상괴간적상사정도,병계산기우해각향이성고사창적NLM결과。결합SURE준칙래융합불동방향적각향이성고사창적비국부평균결과,획득최종적SAR도상강반결과。침대다폭SAR도상진행대비실험,실험결과표명:해방법재유효억제SAR도상상간반적동시능흔호지보류도상적궤하결구신식,위후속적SAR도상리해여해역제공료량호적기출。
Aimed at the shortage of similar region capture and directional information obtainment for SAR image despeckling using conventional non-local means method (NLM), a new NLM SAR image despeckling method is proposed based on multiple different directional anisotropic Gaussian directional window and Stein unbiased risk estimation (SURE) aggregation. The ratio measurement strategy is utilized to compute the similarity of two patches and the NLM result is computed based on the anisotropic Gaussian windows with some direction. The results of NLM with different anisotropic Gaussian windows are aggregated by using the Stein unbiased risk estimation criterion to obtain the final SAR despeckling result. For multiple SAR images, the experiment results show that the new method has advantages in the SAR image despeckling performance, and can well preserve the local geometric structure information, which is essential for understanding and interpretation of SAR image.