Traditional Median Filtering Algorithm Research Articles

A Three-Dimensional Diffusion Filtering Model Establishment and Analysis for Point Cloud Intensity Noise

To improve the quality of point cloud data, as well as maintain edge and detail information in the course of filtering intensity data, a three-dimensional (3D) diffusion filtering equation based on the general principle of diffusion filtering is established in this paper. Moreover, we derive theoretical formulas for the scale parameter and maximum iteration number and achieve self-adaptive denoising, fine control of the point cloud filtering, and accurate prediction of the diffusion convergence. Through experiments with three types of typical point cloud intensity data, the theoretical formulas for the scale parameter and iteration number are verified. Comparative experiments with point cloud data of different types show that the 3D diffusion filtering method has significant denoising and edge-preserving abilities. Compared with the traditional median filtering algorithm, the signal-to-noise ratio (SNR) of the point cloud after filtering is increased by an average of 10% and above, with a maximum value of 40% and above.

A Median Filtering Algorithm Based on Extremum Detection

In this paper a improved algorithm of median filtering based on extremum detection is introduced. According to the deficiencies of the extreme median filtering method in the two stages of noise detection and noise filtering, Adds a false detection noise pixel gray value correction recovery process. Experimental results show that the algorithm in this paper are superior than traditional median filtering algorithm and some improved image filtering algorithm in noise removal and edge retention.

The Median Filtering Algorithm’s Fast Implementation in FPGA

Based on FPGA’S Balance and exchange principle of area and speed, Using the FPGA internal rich logic resources and powerful hardware characteristics , the traditional median filtering algorithm is reduced to 2 clock cycle , Greatly improving the image processing speed . And by using threshold, in a certain extent, reducing the image fuzzy phenomena brought by the median filter . The results of test show that the system runs stability, the time of achieving the median filtering algorithm are narrowed to the shortest clock cycle.