CAJ | 학술논문

针对图像去噪过程存在边缘保持与噪声抑制的矛盾，提出一种改进的偏微分方程图像降噪算法。将差分曲率引入各项异性扩散方程中，构造出新的扩散系数函数，其可以较好区分图像的边缘、平坦区域以及噪声，使算法在去除噪声的同时，保留更多弱边缘和纹理等细节信息。实验结果表明，该算法与其它基于偏微分方程的图像降噪算法相比，在客观的质量评价方面，提高了图像的信噪比和峰值信噪比；在主观视觉效果方面，在滤除噪声的同时保留了更多的弱边缘等细节信息，该算法实现了较好的图像降噪效果。
침대도상거조과정존재변연보지여조성억제적모순，제출일충개진적편미분방정도상강조산법。장차분곡솔인입각항이성확산방정중，구조출신적확산계수함수，기가이교호구분도상적변연、평탄구역이급조성，사산법재거제조성적동시，보류경다약변연화문리등세절신식。실험결과표명，해산법여기타기우편미분방정적도상강조산법상비，재객관적질량평개방면，제고료도상적신조비화봉치신조비；재주관시각효과방면，재려제조성적동시보류료경다적약변연등세절신식，해산법실현료교호적도상강조효과。
Concerning the contradiction between edge‐preserving and noise‐suppressing in the process of image denoising ,an im‐proved partial differential equation (PDE) for image denoising was proposed .Difference curvature was combined with anisotropic diffusion equation ,and a new diffusion coefficient function was constructed .As the new diffusion coefficient function effectively distinguished edges from ramp regions and isolated noise ,the model preserved more details such as weak edges and textures while getting rid of the noise .Experimental results show that ,compared with other image denoising methods based on PDE ,the proposed method improves signal‐to‐noise ratio (SNR) and peak‐signal‐to‐noise ratio (PSNR) in the terms of objective quality evaluation ,and preserves more detail information such as weak edges while removing the noise on the aspect of subjective visual effect .Therefore ,the presented algorithm obtains better image denoising results .