提出一种新的基于非局部均值的多模图像滤波方法。在该方法中,对于噪声图像滤波采用非局部均值方法,其中对于噪声图像块之间灰度相似测度权重由另一幅图像引导计算。实验结果表明,该方法比基于局部的图像去噪方法如双边滤波算法有更好地去噪效果。通过构造联合积分图像对提出算法进行加速,与原始算法相比其显著提速两个数量级,加速算法的复杂度不受滤波器大小影响,易于在并行系统中实现。
In this paper, a novel non-local averaging based multimodal image filtering method is provided. In the method, the mean average for filtering the noisy image is computed non-locally and weights for average is jointly guided by the reference image taken from another imaging device. The experiment results show that the proposed method is better than state of the art joint bilateral filter, especially in the case of the periodic texture is involved in the images. Furthermore, an acceleration algorithm is proposed by constructing integral histograms, speeding up by factor of about 2 order compared with the brute-force method. In addition, the algorithm is independent of the size of the filter, and easy to be implemented on parallel system.