Hybrid Sensor Network Data Compression with Error Resiliency

Kwan, Chiman; Luk, Yvonne

doi:10.1109/dcc.2018.00069

Cited by 10 publications

(9 citation statements)

References 1 publication

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“…Here, we compared our algorithm with another one called BMA (Boundary Matching Algorithm) [9]. It should also be noted that all frames have corrupted pixels.…”

Section: Video Error Concealment Resultsmentioning

confidence: 99%

“…All the matched motion estimations should have similar underlying image structures and the completed version of these patches should lie in a low dimensional subspace. Therefore, the constructed matrix becomes a very low-rank structure and low-rank techniques [1,3,4,7,9,10,12,15,17,18,19,21,24,28,30] can be applied for reconstruction.…”

Section: Principle Of Video Error Concealment [2]mentioning

confidence: 99%

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Perceptually Lossless Video Compression with Error Concealment

Kwan

Shang

Tran

2018

Proceedings of the 2nd International Conference on Vision, Image and Signal Processing

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We present a video compression framework that has several components. First, we aim at achieving perceptually lossless compression. Several well-known video codecs in the literature have been evaluated and the performance was assessed using several well-known performance metrics. Second, we investigated the impact of error concealment algorithms for handling corrupted pixels due to transmission errors in communication channels. Extensive experiments using actual videos have been performed to demonstrate the proposed framework.

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“…Here, we compared our algorithm with another one called BMA (Boundary Matching Algorithm) [9]. It should also be noted that all frames have corrupted pixels.…”

Section: Video Error Concealment Resultsmentioning

confidence: 99%

Section: Principle Of Video Error Concealment [2]mentioning

confidence: 99%

Perceptually Lossless Video Compression with Error Concealment

Kwan

Shang

Tran

2018

Proceedings of the 2nd International Conference on Vision, Image and Signal Processing

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“…On the other hand, pre-processing is used in a variety of applications [30]. A closely relevant example is CM in aviation, where it is found that collected raw data do not provide any additional information [37].…”

Section: Immediate Processing and Actuation Without Transmissionmentioning

confidence: 99%

Vibration Edge Computing in Maritime IoT

Michala

Vourganas

Coraddu

2021

ACM Trans. Internet Things

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IoT and the Cloud are among the most disruptive changes in the way we use data today. These changes have not significantly influenced practices in condition monitoring for shipping. This is partly due to the cost of continuous data transmission. Several vessels are already equipped with a network of sensors. However, continuous monitoring is often not utilised and onshore visibility is obscured. Edge computing is a promising solution but there is a challenge sustaining the required accuracy for predictive maintenance. We investigate the use of IoT systems and Edge computing, evaluating the impact of the proposed solution on the decision making process. Data from a sensor and the NASA-IMS open repository were used to show the effectiveness of the proposed system and to evaluate it in a realistic maritime application. The results demonstrate our real-time dynamic intelligent reduction of transmitted data volume by without sacrificing specificity or sensitivity in decision making. The output of the Decision Support System fully corresponds to the monitored system's actual operating condition and the output when the raw data are used instead. The results demonstrate that the proposed more efficient approach is just as effective for the decision making process.

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“…The first three or six principal components are retained. PCA has the optimal compression performance than others [16]- [21].  JPEG [9] -JPEG is the very first image compression standard which was initially released in 1992.…”

Section: Proposed Multispectral Image Compression Frameworkmentioning

confidence: 99%

Compression Algorithm Selection for Multispectral Mastcam Images

Kwan¹,

Larkin²,

Budavari³

et al. 2019

SIPIJ

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The two mast cameras (Mastcam) onboard the Mars rover, Curiosity, are multispectral imagers with nine bands in each camera. Currently, the images are compressed losslessly using JPEG, which can achieve only two to three times compression. We present a two-step approach to compressing multispectral Mastcam images. First, we propose to apply principal component analysis (PCA) to compress the nine bands into three or six bands. This step optimally compresses the 9-band images through spectral correlation between the bands. Second, several well-known image compression codecs, such as JPEG, JPEG-2000 (J2K), X264, and X265, in the literature are applied to compress the 3-band or 6-band images coming out of PCA. The performance of different algorithms was assessed using four well-known performance metrics. Extensive experiments using actual Mastcam images have been performed to demonstrate the proposed framework. We observed that perceptually lossless compression can be achieved at a 10:1 compression ratio. In particular, the performance gain of an approach using a combination of PCA and X265 is at least 5 dBs in terms peak signal-to-noise ratio (PSNR) at a 10:1 compression ratio over that of JPEG when using our proposed approach.

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Hybrid Sensor Network Data Compression with Error Resiliency

Cited by 10 publications

References 1 publication

Perceptually Lossless Video Compression with Error Concealment

Perceptually Lossless Video Compression with Error Concealment

Vibration Edge Computing in Maritime IoT

Compression Algorithm Selection for Multispectral Mastcam Images

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