Fast median filtering algorithm based on FPGA

Wei, Pingjim; Zhang, Liang; Ma, Chunguang; Yeo, Tat‐Soon

doi:10.1109/icosp.2010.5655365

Cited by 11 publications

(5 citation statements)

References 1 publication

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“…It can remove and suppress a variety of random noises, so the detailed information of the signal can be well protected. Compared with linear smoothing filters, median filtering can maintain clear waves with the same size of filter window [23][24][25][26][27]. The mid-value reflects the concentration of a set of data, which can report the true value of experimental data better than the mean value.…”

Section: Median Filtering Algorithmmentioning

confidence: 99%

Measurement of sound velocity in oil wells based on fast adaptive median filtering

Zhou¹,

Liu²,

Gan³

2020

Turk J Elec Eng & Comp Sci

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Measurement of sound velocity in oil wells has long been a challenging industrial issue due to the difficulty in obtaining clear oil pipe coupling waves in strong noise. In this paper, a novel sound velocity measurement method is developed for the dynamic liquid level of oil wells based on fast adaptive median filtering. First, to solve the noise interference problem in the reflected oil pipe coupling wave, a fast adaptive median filtering algorithm is proposed to obtain an accurate oil pipe coupling wave. Then a curve fitting method based on range discrete coefficient is developed to estimate the sound velocity in the tubing-casing annular space of oil wells. The fitting sound velocity can reflect the propagation rule of the real sound velocity. In particular, the sound velocity at any position within the tubing-casing annular space can be accurately calculated by the fitting function. Finally, the proposed method is applied to the dynamic liquid level of an oil well. Experimental results show the effectiveness and favorable accuracy in estimating the sound velocity distribution.

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Section: Median Filtering Algorithmmentioning

confidence: 99%

Measurement of sound velocity in oil wells based on fast adaptive median filtering

Zhou¹,

Liu²,

Gan³

2020

Turk J Elec Eng & Comp Sci

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“…In order to improve the performance of image filtering, adaptive filter is proposed which is capable to encounter the issues related to impulsive noise. Moreover, the adaptive median Pingjun Wei et al [12] presented another study based on the adaptive median filtering. In their study they show that median filtering can perform image filtering if rectangular blocks are provided as an input.…”

Section: Related Workmentioning

confidence: 99%

An Image Enhancement Approach to Achieve High Speed Using Adaptive Modified Bilateral Filter for Satellite Images Using FPGA

Panchacharam¹,

M.N²

2017

TELKOMNIKA

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For real time application scenarios of image processing, satellite imaginary has grown more interest by researches due to the informative nature of image. Satellite images are captured using high quality cameras. These images are captured from space using on-board cameras. Wrong ISO setting, camera vibrations or wrong sensory setting causes noise. The degraded image can cause less efficient results during visual perception which is a challenging issue for researchers. Another reason is that noise corrupts the image during acquisition, transmission, interference or dust particles on the scanner screen of image from satellite to the earth stations. If quality degraded images are used for further processing then it may result in wrong information extraction. In order to cater this issue, image filtering or denoising approach is required.Since remote sensing images are captured from space using on-board camera which requires high speed operating device which can provide better reconstruction quality by utilizing lesser power consumption. Recently various approaches have been proposed for image filtering. Key challenges with these approaches are reconstruction quality, operating speed, image quality by preserving information at edges on image.Proposed approach is named as modified bilateral filter. In this approach bilateral filter and kernel schemes are combined. In order to overcome the drawbacks, modified bilateral filtering by using FPGA to perform the parallelism process for denoising is implemented.

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“…A common related application is median filtering for noise removal in image processing, which usually entails small two-dimensional windows and assumes 8-bit integer representations. These constraints are exploited to allow fast comparison networks [4][5] or histogram implementations [6]. Radar OS-CFAR applications require longer window lengths and greater dynamic range (such as single-precision floating point numbers), and thus cannot take advantage of these approaches.…”

Section: Fpga Implementationsmentioning

confidence: 99%

Real-time implementations of ordered-statistic CFAR

Bales

Benson

Dickerson

et al. 2012

2012 IEEE Radar Conference

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Abstract-Ordered-statistic constant false alarm rate (OS-CFAR) detectors provide improved robustness over cellaveraging CFAR (CA-CFAR) detectors in multiple target and heterogeneous clutter environments. However, this benefit comes at the cost of generally increased processing time due to the need for a rank-ordering of the CFAR training data. Realtime implementations of OS-CFAR must consider this additional processing burden.In this paper, we present real-time FPGA and CPU/GPU implementations of OS-CFAR. A novel sorting architecture that scales linearly with window size is presented alongside traditional compare-and-swap and rank-only architectures in an FPGA. A rank-only GPU implementation is demonstrated alongside multi-threaded sorting and rank-only CPU implementations. Effects of training window size on throughput and power consumption are considered.

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Fast median filtering algorithm based on FPGA

Cited by 11 publications

References 1 publication

Measurement of sound velocity in oil wells based on fast adaptive median filtering

Measurement of sound velocity in oil wells based on fast adaptive median filtering

An Image Enhancement Approach to Achieve High Speed Using Adaptive Modified Bilateral Filter for Satellite Images Using FPGA

Real-time implementations of ordered-statistic CFAR

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