An approach towards a full-reference-based benchmarking for quality-optimized endoscopic video stabilization systems

2012 ◽  
Author(s):  
Marvin C. Offiah ◽  
Navya Amin ◽  
Thomas Gross ◽  
Nail El-Sourani ◽  
Markus Borschbach
Keyword(s):  
Video Stabilization ◽  
Full Reference ◽  
Endoscopic Video

Single Image Dehazing by Predicting Atmospheric Scattering Parameters

2020 ◽  
Vol 2020 (1) ◽  
pp. 74-77
Author(s):  
Simone Bianco ◽  
Luigi Celona ◽  
Flavio Piccoli
Keyword(s):  
Reference Image ◽  
Single Image ◽  
Scattering Parameters ◽  
Image Dehazing ◽  
Atmospheric Scattering ◽  
Local Structures ◽  
Full Reference ◽  
Reconstruction Quality ◽  
Single Image Dehazing

In this work we propose a method for single image dehazing that exploits a physical model to recover the haze-free image by estimating the atmospheric scattering parameters. Cycle consistency is used to further improve the reconstruction quality of local structures and objects in the scene as well. Experimental results on four real and synthetic hazy image datasets show the effectiveness of the proposed method in terms of two commonly used full-reference image quality metrics.

Image Stitching Algorithms - A Review

2016 ◽  
Vol 1 (2) ◽  
pp. 14-18
Author(s):  
Srishty Suman ◽  
Utkarsh Rastogi ◽  
Rajat Tiwari
Keyword(s):  
Video Compression ◽  
Video Summarization ◽  
Video Stabilization ◽  
Image Stitching

Image stitching is the process of combining two or more images of the same scene as a single larger image. Image stitching is needed in many applications like video stabilization, video summarization, video compression, panorama creation. The effectiveness of image stitching depends on the overlap removal, matching of the intensity of images, the techniques used for blending the image. In this paper, the various techniques devised earlier for the image stitching and their applications in the relative places has been reviewed.

Research Roundup

2020 ◽  
Vol 31 (7) ◽  
pp. 310-311
Author(s):  
George Winter
Keyword(s):  
Practice Nurses ◽  
Full Reference

George Winter provides an overview of recently published articles that may be of interest to practice nurses. Should you wish to look at any of the papers in more detail, a full reference is provided.

scholarly journals A New Application-Aware No-Reference Quality Assessment Method for IP Voice Services

2021 ◽  
Vol 29 (3) ◽  
Author(s):  
Péter Orosz ◽  
Tamás Tóthfalusi
Keyword(s):  
Service Quality ◽  
Performance Metrics ◽  
Assessment Method ◽  
Reference Source ◽  
User Privacy ◽  
Quality Model ◽  
Estimation Model ◽  
Full Reference ◽  
Reference Quality ◽  
The Voice

AbstractThe increasing number of Voice over LTE deployments and IP-based voice services raise the demand for their user-centric service quality monitoring. This domain’s leading challenge is measuring user experience quality reliably without performing subjective assessments or applying the standard full-reference objective models. While the former is time- and resource-consuming and primarily executed ad-hoc, the latter depends upon a reference source and processes the voice payload that may offend user privacy. This paper presents a packet-level measurement method (introducing a novel metric set) to objectively assess network and service quality online. It is accomplished without inspecting the voice payload and needing the reference voice sample. The proposal has three contributions: (i) our method focuses on the timeliness of the media traffic. It introduces new performance metrics that describe and measure the service’s time-domain behavior from the voice application viewpoint. (ii) Based on the proposed metrics, we also present a no-reference Quality of Experience (QoE) estimation model. (iii) Additionally, we propose a new method to identify the pace of the speech (slow or dynamic) as long as voice activity detection (VAD) is present between the endpoints. This identification supports the introduced quality model to estimate the perceived quality with higher accuracy. The performance of the proposed model is validated against a full-reference voice quality estimation model called AQuA, using real VoIP traffic (originated in assorted voice samples) in controlled transmission scenarios.

scholarly journals DL-based segmentation of endoscopic scenes for mitral valve repair

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Matthias Ivantsits ◽  
Lennart Tautz ◽  
Simon Sündermann ◽  
Isaac Wamala ◽  
Jörg Kempfert ◽  
...  
Keyword(s):  
Mitral Valve ◽  
Minimally Invasive ◽  
Mitral Valve Repair ◽  
Video Stream ◽  
Field Of View ◽  
Valve Repair ◽  
Distance Measurements ◽  
Anatomical Structures ◽  
Endoscopic Video ◽  
Camera Position

AbstractMinimally invasive surgery is increasingly utilized for mitral valve repair and replacement. The intervention is performed with an endoscopic field of view on the arrested heart. Extracting the necessary information from the live endoscopic video stream is challenging due to the moving camera position, the high variability of defects, and occlusion of structures by instruments. During such minimally invasive interventions there is no time to segment regions of interest manually. We propose a real-time-capable deep-learning-based approach to detect and segment the relevant anatomical structures and instruments. For the universal deployment of the proposed solution, we evaluate them on pixel accuracy as well as distance measurements of the detected contours. The U-Net, Google’s DeepLab v3, and the Obelisk-Net models are cross-validated, with DeepLab showing superior results in pixel accuracy and distance measurements.

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