Uncertain active contour model based on rough and fuzzy sets for auroral oval segmentation

Shi, Jiao; Lei, Yu; Wu, Jiaji; Jeon, Gwanggil

doi:10.1016/j.ins.2019.04.017

Cited by 10 publications

(1 citation statement)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The desired demosaicking method must take advantage of high visual quality images with low complexity. To accomplish this task, many researchers have been studied various demosaicking methods [8][9][10][11][12][13][14][15]. Most existent demosaicking algorithms usually concentrate upon how to precisely discover the minimum variation direction in the mosaicked CFA image.…”

Section: Introductionmentioning

confidence: 99%

Image enhancement in embedded devices for internet of things

Jeon

Pasupa

Anisetti

et al. 2019

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

This paper proposes a new color interpolation method which can be used in embedded devices for IoT system. In this work, we use regression approach for generating and designing filters to restore color image. The filters are designed with four sizes, 5x5 training filter, 7x7 training filter, 9x9 training filter, and 11x11 training filter. The obtained filters are tested in 25 LC dataset to assess the performance.Experimental results inform that the proposed filters provide outstanding performance when they are compared with conventional methods. As compared with the other methods, the proposed filters produce the best average interpolation performance both objectively and visually.

show abstract

Section: Introductionmentioning

confidence: 99%

Image enhancement in embedded devices for internet of things

Jeon

Pasupa

Anisetti

et al. 2019

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

show abstract

Structure and gradient‐based industrial interpolation using computational intelligence

Jeon

2019

Concurrency and Computation

View full text Add to dashboard Cite

SummaryIndustry and medical imaging are technologies and processes of managing subjective representations of the industry product, interior of a body for analyzing. The deinterlacing is the procedure of transforming interlaced signal into progressive one. In this paper, I propose a new single field deinterlacing method which has three sub‐methods: bilinear method, small filter‐based method, and large filter‐based method. Pixels in a given image are grouped into three regions by calculated local mean and variance values: stable region, neutral region, and complex region. To implement deinterlacing process, I use weight average filter by considering two factors (the likeness factor and the distance factor) and determine region characteristics. Simulation results inform that the presented method yields satisfactory results in objective metrics (PSNR, SSIM, implementation time) and subjective quality.

show abstract

Non-dominated Sorting Genetic Algorithm (NSGA)-III Based Fuzzy Segmentation Model

Kumari¹,

Kumar

2020

Algorithms for Intelligent Systems

View full text Add to dashboard Cite

Uncertain active contour model based on rough and fuzzy sets for auroral oval segmentation

Cited by 10 publications

References 40 publications

Image enhancement in embedded devices for internet of things

Image enhancement in embedded devices for internet of things

Structure and gradient‐based industrial interpolation using computational intelligence

Non-dominated Sorting Genetic Algorithm (NSGA)-III Based Fuzzy Segmentation Model

Contact Info

Product

Resources

About