基于小波前向后向扩散的红外图像降噪与边缘增强算法
doi: 10.3724/SP.J.1146.2006.00993
Wavelet Forward and Backward Diffusion for Infrared Image Denoising and Edge Enhancement
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摘要: 针对红外图像特点，该文提出了一种基于小波前向后向扩散的红外图像降噪与边缘增强算法。小波前向后向扩散是建立在小波扩散理论的基础上，其继承了小波扩散迭代降噪与边缘保持特性，在此基础上实现了图像的边缘增强。为了克服传统小波扩散基于小波模值的边缘映射的不足，该文利用小波模值与局部奇异性测度的联合概率分布对边缘映射进行初步估计，结合几何约束进行修正，获得准确的边缘映射，并重新设计了小波前向后向扩散系数方程。实验证明算法能有效实现红外图像降噪的同时增强图像边缘。Abstract: To achieve infrared image denoising and edge enhancement, a method based on wavelet forward and backward diffusion is introduced. Wavelet forward and backward diffusion is based on wavelet diffusion theory. It not only inherites iterative noise reduction and edge preserving features from wavelet diffusion, but also enhancemented image edge at the same time. In order to solve the problem of using wavelet modulus, it uses both wavelet modulus and local regularity to get elementary edge map, then get accurate edge map with geometric consistency and redesign wavelet forward and backward diffusion equation. Experiment shows that the method can effectively realize infrared image denoising and edge enhancement.
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