A recursive modified Gaussian filter for impulse noise removal

Roomi, S. Md. Mansoor; Lakshmi, I.M.; Kumar, Vikas

doi:10.1049/cp:20060590

Cited by 7 publications

(3 citation statements)

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“…2) Gaussian-based smoothing: The Gaussian filter has been a de-facto standard for applications such as image processing and computer vision. A Gaussian function for one dimensional data is [19]:…”

Section: B the Proposed Algorithm Vs Moving Average 1)mentioning

confidence: 99%

Gaussian-Based Smoothing of Wind and Solar Power Productions Using Batteries

Desta

Courbin²,

Sciandra³

et al. 2017

IJMERR

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Intermittent nature of Distributed Energy Resources (DER) such as solar and wind cause significant power fluctuations and integrating them to a power systems requires control mechanisms to reduce fluctuations. One way to control the effect of fluctuation is to use Energy Storage Systems (ESS) for smoothing out their power productions. A typical method to attain this goal is to use ESS with classical moving average approaches. However, these methods are affected by peaks and troughs in power production due to cloud passing and wind gust effects on solar panels and wind turbines, respectively. In this paper, we propose a Gaussian-based smoothing method to alleviate pitfalls of moving average methods to smooth out forecasted values of solar and wind powers. Then, we determine a minimum ESS size required to maintain a smoothed power curve for a day-ahead period. From our experiments, the proposed algorithm requires smaller ESS size than the classical approaches. 

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Section: B the Proposed Algorithm Vs Moving Average 1)mentioning

confidence: 99%

Gaussian-Based Smoothing of Wind and Solar Power Productions Using Batteries

Desta

Courbin²,

Sciandra³

et al. 2017

IJMERR

View full text Add to dashboard Cite

show abstract

“…As the mean filters are implemented uniformly across the image, they tend to modify both noisy as well as good pixels. To avoid damage to the good pixels, a switching scheme has been introduced as reported in [3][4][5][6][7] where noise pixel isolation algorithms are employed before filtering and the detection results are used to decide whether the pixel is to be modified or not. Two image sequences are generated during the speckle detection procedure.…”

Section: B Mathematical Modeling Of Cnlmm Filtermentioning

confidence: 99%

“…The use of multilook processing to fetal images usually results in poor performance, since it suppresses both the speckle and the texture information of clinical importance at the same time. In the recent past, numerous speckle suppression filters have been proposed for enhancing fetal structures which include the median [2], Lee [3], Kuan [4], Frost [5], Hybrid median [6], SRAD [7], Relaxed median [9], and Homomorphic [10]. Each speckle reduction filter is designed based on different criteria and parameters.…”

Section: Introductionmentioning

confidence: 99%