Abstract—As a rule, modern methods of improving and contrasting image details are based on the edge-preserving filters or bilateral filters. However, the computational complexity of classic bilateral filters is proportional to the square of the number of pixels in the image and fast algorithms are not always efficient enough or the filtering result does not always match the result of the original filter. We propose replacing the classic bilateral filter with a geodesic distance filter, which also belongs to the class of convolution transformations that can improve visual perception of images using information about the edges of objects in the processed image. The convolution kernel based on the geodesic distance has several advantages, as it allows recursive computation and, therefore, fast image processing. We also propose a method for suppressing color artifacts by switching from the standard RGB representation to the HSV representation, which is more balanced with respect to the perception of human vision. The effectiveness of the proposed filter is compared using the illustrations to this article so that the reader can visually compare the qualities of various processing options.

摘要—通常，改进和对比图像细节的现代方法是基于边缘保留滤镜或双边滤镜的。但是，经典双边滤波器的计算复杂度与图像中像素数量的平方成比例，并且快速算法并不总是足够有效，或者滤波结果并不总是与原始滤波器的结果匹配。我们建议用测地距离过滤器代替经典的双边过滤器，该过滤器也属于卷积变换类，它可以使用有关处理后图像中对象边缘的信息来改善图像的视觉感知。基于测地距离的卷积核具有多个优点，因为它允许递归计算，因此可以进行快速图像处理。我们还提出了一种通过从标准RGB表示切换到HSV表示来抑制颜色伪影的方法，该方法相对于人类视觉的感知更加平衡。使用插图与本文比较了所提出的过滤器的有效性，以便读者可以直观地比较各种处理选项的质量。