基于数据融合的多尺度图像去噪方法
A Novel Multiscale Image Denoising Algorithm Based on Image Fusion
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摘要: 将图像系数尺度内相关模型较强的去噪能力与尺度间相关模型保持边缘的优越性能相结合,提出了一种新的基于数据融合的多尺度图像去噪方法。同时引入了一种新的基于结构相似性(SSIM)指数的图像质量标准来衡量初始去噪图像和融合后图像与原始图像的相似程度,评估图像保持边缘和去噪的能力。仿真结果表明,基于数据融合的方法具有更好的视觉效果和去噪性能Abstract: A novel multiscale image denoising method based on image fusion is proposed,which combines high denoising ability of the intrascale statistical model with better performance of edge preservation of the interscale model.And we introduce a novel image assessment measure based on structural similarity(SSIM) index to evaluate the equality of original denoised images and fusion image.Simulation results show that the proposed method has better visual effect and high denoising quality.
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