Improved Median Filter Algorithm Research Articles

Quick Median Filtering Algorithms Based on FPGA

Median filtering is an important approach in digital image processing for noise elimination. An improved median filtering algorithm (IMFA) is proposed which can be implemented with only 17 comparisons and 6 clocks delay for 3×3 median filtering mathematical model based on field programmable gate array (FPGA). The algorithm benefits from the parallel processing and pipelining structure of FPGA hardware. At first, the characteristics, basic operational principle and computing process of the IMFA are presented. And then the algorithm using modular technique and top-down design flow methodology with Verilog HDL are programed. At last, some simulation verifications for the algorithm by ModelSim and experimental verification on FPGA hardware platform are carried out. The IMFA can get a large number of data throughput and more quickly processing speed and less hardware resources than similar filtering algorithms.

Improved Median Filtering Algorithm Based on FPGA

Aiming at the loss of image boundary information and the blurred image details in the classical median filtering algorithm, the improved median filtering algorithm based on FPGA (Field Programmable Gate Array) is proposed. In the improved median filtering algorithm, the borders mirroring and threshold comparing are adopted, and the loss of the image boundary information is lowed and the detailed information of image is preserved. The improved median filtering algorithm based on FPGA consists of the filter template generating module, the median grayscale computing module and threshold comparing module. The experimental results show that that the NMSE (normalized mean square errors) of the image filtered with the improved median filtering algorithm is lowed by 25.6%, and the operating efficiency is improved by 16% comparing with the classical median filtering algorithm.

Application of Improved Median Filtering Algorithm to Image De-Noising

Based on the shortcomings of standard median filtering and combined with the mean filtering, this paper puts forward two improved median filtering algorithms referred as the weighted fast median filtering algorithm and the weighted adaptive median filtering algorithm. The experiment results with MATLAB show that weighted fast median filtering algorithm has a significant effect on low-density impulse noise, and accelerates the speed of real-time processing. The weighted median filter could effectively eliminate the high-density impulse noise from polluted images, and better maintains the details of the original image.