计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
12期
188-193,206
,共7页
合成孔径雷达%图像去噪%非下采样轮廓变换%邻域收缩
閤成孔徑雷達%圖像去譟%非下採樣輪廓變換%鄰域收縮
합성공경뢰체%도상거조%비하채양륜곽변환%린역수축
Synthetic Aperture Radar(SAR)%image denoising%Nonsubsampled Contourlet Transform(NSCT)%NeighShrink
针对合成孔径雷达(Synthetic Aperture Radar,SAR)图像受到相干斑噪声的干扰,严重影响了SAR图像的后续处理的问题,提出一种在非下采样轮廓变换(Nonsubsampled Contourlet Transform,NSCT)域将中值滤波和邻域收缩法相结合的SAR图像去噪算法。该算法对原始SAR图像进行NSCT分解,得到低频子带和高频子带图像,对低频子带使用中值滤波处理以去除低频子带中的低频噪声,利用NSCT分解系数之间的相关性,使用邻域收缩法对子带图的系数进行收缩,以消除高频子带中的高频噪声。实验证明,该算法与小波域邻域收缩去噪算法和NSCT硬阈值去噪算法相比,在去噪性能和视觉效果方面均有所提高,在消除噪声同时可以较好地保护纹理细节信息。
針對閤成孔徑雷達(Synthetic Aperture Radar,SAR)圖像受到相榦斑譟聲的榦擾,嚴重影響瞭SAR圖像的後續處理的問題,提齣一種在非下採樣輪廓變換(Nonsubsampled Contourlet Transform,NSCT)域將中值濾波和鄰域收縮法相結閤的SAR圖像去譟算法。該算法對原始SAR圖像進行NSCT分解,得到低頻子帶和高頻子帶圖像,對低頻子帶使用中值濾波處理以去除低頻子帶中的低頻譟聲,利用NSCT分解繫數之間的相關性,使用鄰域收縮法對子帶圖的繫數進行收縮,以消除高頻子帶中的高頻譟聲。實驗證明,該算法與小波域鄰域收縮去譟算法和NSCT硬閾值去譟算法相比,在去譟性能和視覺效果方麵均有所提高,在消除譟聲同時可以較好地保護紋理細節信息。
침대합성공경뢰체(Synthetic Aperture Radar,SAR)도상수도상간반조성적간우,엄중영향료SAR도상적후속처리적문제,제출일충재비하채양륜곽변환(Nonsubsampled Contourlet Transform,NSCT)역장중치려파화린역수축법상결합적SAR도상거조산법。해산법대원시SAR도상진행NSCT분해,득도저빈자대화고빈자대도상,대저빈자대사용중치려파처리이거제저빈자대중적저빈조성,이용NSCT분해계수지간적상관성,사용린역수축법대자대도적계수진행수축,이소제고빈자대중적고빈조성。실험증명,해산법여소파역린역수축거조산법화NSCT경역치거조산법상비,재거조성능화시각효과방면균유소제고,재소제조성동시가이교호지보호문리세절신식。
Speckle noise in Synthetic Aperture Radar(SAR)images seriously affects the subsequent processing of the SAR image. In order to solve this problem, a denoising method is presented for SAR image which combines median filter-ing and NeighShrink based on nonsubsampled contourlet transform. The original SAR image is decomposed by NSCT to get the low-frequency subband and high-frequency subband image, and then low-frequency noise in the low-frequency subband is removed by using the median filter. According to the correlation neighbouring coefficients of NSCT decompo-sition, the high-frequency noise in the high-frequency subband is eliminated by using NeighShrink. Experimental results show that this approach is better than the NeighShrink based on wavelet and the NSCT hard threshold denoising method in denoising performance and visual effects. The proposed denoising method can improve capability in speckle denoising and can protect the texture message better.