Multi-Focus Image Fusion Algorithm in Sensor Networks

Tong, Ying; Chen, Jin

doi:10.1109/access.2018.2866020

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…The consequences of the reproduction tests demonstrate that our calculation is compelling and outflanks some cutting edge algorithms. [5]…”

Section: Literature Surveymentioning

confidence: 99%

An Adaptive Wavelet based Fusion Approach for Efficient Image Restoration

Kumari¹,

Rawat²

2018

IJCA

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Nowadays lots of work is going to be done on the field of image fusion and also used in various application such as medical imaging and multi spectra sensor image fusing etc. For fusing the image various techniques has been proposed by different previous works such as wavelet transform, IHS (Intensity, Hue and Saturation) and Principal Component Analysis (PCA), based methods etc. In this paper literature of the image fusion is discussed with implementation using wavelet transform used for the specific application as in the image restoration field. Using Image fusion may improve the perceptual quality of the restored images. Usually image deblurring methods are used at the front end for restoration and then image fusion is used for improving the visual quality. Paper uses three de-blurring technique to blindly restoring the image then use statistical parameters for adopting the best fused images out of various hybrid fusion results. Performance is tested on images with distinct features.

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“…The consequences of the reproduction tests demonstrate that our calculation is compelling and outflanks some cutting edge algorithms. [5]…”

Section: Literature Surveymentioning

confidence: 99%

An Adaptive Wavelet based Fusion Approach for Efficient Image Restoration

Kumari¹,

Rawat²

2018

IJCA

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“…It is worth mentioning that IoAV applications have evolved three times according to three main phases as presented in Figure 1: Embedded autopilot: In this phase, the original equipment manufacturer (OEM) executes the entire autopilot at the vehicle. Tesla and Hyundai are examples of proprietary embedded autopilots 10,11 . The main stakeholders involved in this phase are OEMs, embedded service function providers and end users. Edge assist: In this phase, the CAV has no embedded autopilot while the edge has virtual autopilots running for each connected vehicle.…”

Section: Introductionmentioning

confidence: 99%

“…Tesla and Hyundai are examples of proprietary embedded autopilots. 10,11 The main stakeholders involved in this phase are OEMs, embedded service function providers and end users. 2.…”

Section: Introductionmentioning

confidence: 99%

6G‐edge support of Internet of Autonomous Vehicles: A survey

Ibn‐Khedher,

Laroui,

Alfaqawi

et al. 2023

Trans Emerging Tel Tech

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With the commercial deployment of 5G mobile communication systems, 6G is proposed to meet the needs of new use cases including connected and autonomous vehicles (CAVs). In this article, we surveyed different 6G embracing technologies such as mobile edge computing, unmanned aerial vehicles, network function virtualization, software defined networking, and artificial intelligence that can enhance the Internet of Autonomous Vehicles (IoAV) network performance comparing to existing 5G enabled solutions. Then, we highlight the convergence path of 6G and IoAV to satisfy the next generation of CAV applications. Further, we propose 6G cellular communication to support the quality of next IoAV applications. Furthermore, the article attempts to study the serious challenges in the 6G‐IoAV research field and propose potential future directions.

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Energy Efficient Multifocus Image Fusion in DCT Domain

Sreeja¹,

Saraniya²

2020

Advances in Intelligent Systems and Computing

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Multi-Focus Image Fusion Algorithm in Sensor Networks

Cited by 5 publications

References 15 publications

An Adaptive Wavelet based Fusion Approach for Efficient Image Restoration

An Adaptive Wavelet based Fusion Approach for Efficient Image Restoration

6G‐edge support of Internet of Autonomous Vehicles: A survey

Energy Efficient Multifocus Image Fusion in DCT Domain

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