DocumentCode
703930
Title
A low energy 2D adaptive median filter hardware
Author
Kalali, Ercan ; Hamzaoglu, Ilker
Author_Institution
Fac. of Eng. & Natural Sci., Sabanci Univ., Istanbul, Turkey
fYear
2015
fDate
9-13 March 2015
Firstpage
725
Lastpage
729
Abstract
The two-dimensional (2D) spatial median filter is the most commonly used filter for image denoising. Since it is a non-linear sorting based filter, it has high computational complexity. Therefore, in this paper, we propose a novel low complexity 2D adaptive median filter algorithm. The proposed algorithm reduces the computational complexity of 2D median filter by exploiting the pixel correlations in the input image, and it produces higher quality filtered images than 2D median filter. We also designed and implemented a low energy 2D adaptive median filter hardware implementing the proposed 2D adaptive median filter algorithm. The proposed hardware is verified to work correctly on a Xilinx Zynq 7000 FPGA board. It can process 105 full HD (1920×1080) images per second in the worst case on a Xilinx Virtex 6 FPGA, and it has more than 80% less energy consumption than original 2D median filter hardware on the same FPGA.
Keywords
adaptive filters; computational complexity; field programmable gate arrays; image denoising; image filtering; image resolution; median filters; 105 full RD image; 2D spatial median filter; Xilinx Zynq 7000 FPGA board; computational complexity; energy consumption; image denoising; low complexity 2D adaptive median filter algorithm; low energy 2D adaptive median filter hardware; nonlinear sorting based filter; pixel correlations; two-dimensional spatial median filter; Adaptive filters; Algorithm design and analysis; Field programmable gate arrays; Filtering algorithms; Hardware; Maximum likelihood detection; Nonlinear filters; FPGA; Median filter; hardware implementation; low energy;
fLanguage
English
Publisher
ieee
Conference_Titel
Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015
Conference_Location
Grenoble
Print_ISBN
978-3-9815-3704-8
Type
conf
Filename
7092482
Link To Document