![]() On graphic, normal distribution is a Bell-shaped curve, the closer to the center, the bigger the value. Normal distribution is an acceptable weight distribution model. Hence the weighted average is more reasonable than simple average, the close the points in distance, the larger the weight. If we just use simple average, it's unreasonable, because images are continuous, the closer the points in distance, the closer the relationship between points. ![]() The question now is if every point will get the average value of surrounding points, then how should we allocate weight? The bigger the blur radius, the more blur the picture is. The above are graphs of original, 3 pixels blur radius and 10 pixels blur radius. Obviously if the value range is very large, the blur effect is very strong. From value perspective, it's a smoothing. The center point will take the average value of its surrounding points, it will be 1. On the above graph, 2 is the center point, the surrounding points are 1. ![]() The so called blur can be understood as taking a pixel as the average value of its surrounding pixels. In fact, it is a kind of data smoothing which can be used in many situations. This article is to introduce Gaussian Blur algorithm, you will find this is a simple algorithm. It utilizes Gaussian distribution to process images. There are many algorithms to implement blur, one of them is called Gaussian Blur Algorithm. Usually, image processing software will provide blur filter to make images blur. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. Archives
December 2022
Categories |