High Throughput VLSI Architecture for One Dimensional Median Filter

Teja, V.V.R.; Ray, Kailash Chandra; Chakrabarti, Indrajit; Dhar, Anindya Sundar

doi:10.1109/icscn.2008.4447215

Cited by 7 publications

(3 citation statements)

References 9 publications

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“…The design is simple, compact yet efficient. Unlike existing implementations of sorting networks [10][11][12][13][14][15][16][17][18][19] that propagate the incoming samples along the window pipelines to compare and swap the samples with the values stored in the window ranks "on the fly", we do not use pipelining. In our design, all values of the window are compared with the incoming sample at once.…”

Section: Contributionmentioning

confidence: 99%

An efficient implementation of 1-D median filter

Moshnyaga

Hashimoto

2009

2009 52nd IEEE International Midwest Symposium on Circuits and Systems

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This paper presents a new architecture and circuit implementation of 1-D median filter. The proposed circuit belongs to the class of non-recursive sorting network architectures that process the input samples sequentially in the word-based manner. In comparison to the related schemes, it maintains sorting of samples from the previous position of the sliding window, positioning only the incoming sample to the correct rank. Unlike existing 1-D filter implementations, the circuit has linear hardware complexity, minimal latency and achieves throughput of 1/2 of the sampling rate. Experimental evaluation and comparisons show high efficiency of our design.

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Section: Contributionmentioning

confidence: 99%

An efficient implementation of 1-D median filter

Moshnyaga

Hashimoto

2009

2009 52nd IEEE International Midwest Symposium on Circuits and Systems

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“…The weighted median filter is used in scan rate conversion in normal Television system. One of the median filter branches is the weighted median filter [11][12][13][14]. The weighted median filter was first presented in 1981.…”

Section: Weighted Median Filtermentioning

confidence: 99%

A new method for designing an efficient switching median filter using VLSI architecture to remove salt and pepper noise

AbdElminaam

Rafiq²,

Muthusamy³

et al. 2022

Journal of Computing and Communication

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Any imaging system's images have dynamic intensity value variations, rapid light shifts, and poor contrast. Such visuals are empty of useful information and difficult to comprehend visually. Filtering methods to eliminate noise, improve contrast, and detect edges are used to retrieve secondary information from such photographs. Median filtering is one of the nonlinear ways that remove the range of isolated noise like salt and pepper noise while preserving the edge information of the image. However, median filtering fails to remove the noise when the image is affected by too strong impulsive noise. The switching median filtering technique can be used to eliminate high-intensity impulse noise. This research presents a VLSI design for a novel switching-based median filter to reduce high-density salt and pepper noise in digital images. The absolute difference between the center pixel and the array median obtained from a 3 x 3 sliding window is compared to a predefined threshold value to determine whether a pixel is noisy or not. During the filtering stage, the noisy pixels in the 3 x 3 filtering window are replaced by the median of noise-free pixels. If a pixel value is damaged, it is replaced with the median of the following window. The true pixel intensity value is kept if the pixel is not destroyed. We can tell if a pixel is corrupted or not by using a threshold detector. We may either add salt and pepper noise to an image directly or create it ourselves. This is a step in the image preparation process. The normal image is uploaded and converted it to a salt and pepper noise image using MATLAB's built-in capabilities. We used three tools in our project. We used MATLAB to preprocess the picture and plot data to reconstruct the original image, then ModelSim to produce the median filter, and XILINX to compare the existing bubble sort to the recommended threecell sorter. The proposed technique outperforms standard median-based filters in simulations and is particularly effective in circumstances where pictures are badly damaged.

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“…In the bit-level architecture, the samples are processed in parallel, and the bits of the incoming samples are sequentially processed [1], [2], [3], [5], [8]. On the contrary, the word-level samples are sequentially processed word by word, and the bits of the sample are processed in parallel [4], [6], [7], [10], [11], [12]. Cadenas et al [1] proposed a novel quantum like representation allowing the median to be computed in an accelerated manner compared to the best-known method.…”

Section: Introductionmentioning

confidence: 99%