.png){kind=icon}
返回
Pixel Difference Function and Local Entropy-Based Speckle Reducing Anisotropic Diffusion
.png){kind=icon}
PRE
AI
DOI：10.1109/TGRS.2022.3182886.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Speckles destroy the texture details of synthetic aperture radar (SAR) images, thereby constraining their high-precision application. Speckle suppression and edge preservation are two aspects that need to be balanced in despeckling. Although a conventional anisotropic diffusion (AD) filter can theoretically achieve this balance, it still triggers many edge losses. To better improve the balance, a novel AD filter based on the pixel difference function (PDF) and local entropy (LE) is proposed. The proposed filter utilizes a PDF to update the original diffusion function of the AD filter and introduces LE to recover the edge loss from the ratio image generated by noisy and filtered images. In addition, a neighborhood weighting approach and a new adaptive iterative rule are proposed for better AD filtering. Simulated data and real SAR images were applied to evaluate the performance of the proposed algorithm. Experimental results show that the proposed filter both effectively smooths speckles and reduces edge loss. Furthermore, the effectiveness and superiority of the proposed method were confirmed by comparison with other state-of-the-art methods.
Keyword:
Image edge detection
Speckle
Optical filters
Filtering theory
Anisotropic magnetoresistance
Radar polarimetry
Mathematical models
Anisotropic diffusion (AD)
filter
local entropy (LE)
pixel difference function (PDF)
speckle
期刊
IF:
8.6
论文数:
2.2W
被引数:
10.7W
机构
引用论文
.png){kind=icon}
分享收藏Fusion Despeckling Based on Surface Variation Anisotropic Diffusion Filter and Ratio Image Filter
PREAI
分享收藏
查看更多内容