【摘要】 本文提出了一种新的图象平滑方法——修正的邻域平均法。这种方法不仅能够有效地平滑噪声,还能够锐化模糊的图象边缘;计算比较简单,不需要任何先验知识和预定的参数。为了定量地评价这种平滑方法的性能,本文对计算机产生的试验图象定义了一种图象优值,作为评价的指标。并且通过实验将这种平滑方法的性能与梯度的倒数加权平均法、中值滤波法进行了比较。最后给出了处理实际照片的结果。更多还原

【Abstract】 In this paper, a new method for image smoothing——the modified neighborhood averaging method is presented. With this method, not only the noise can be smoothed efficiently, but also the blurred edge of an image be sharpened. It is simple in computation, requiring no a priori knowledge and predetermined parameters. In order to evaluate the performance of the proposed method quantitatively, a figure of merit for the test image generated by computer is defined and used as a measure of evaluation. The performance of the method is also compared with that of the gradient inverse weighted smoothing method and median filtering by experiments. Finally, processed results of real world images are given.更多还原