Objective analysis of image quality of video image capture systems

1990 ◽  
Author(s):  
Alan H. Rowberg
Keyword(s):  
Image Quality ◽  
Video Image ◽  
Objective Analysis ◽  
Image Capture

scholarly journals Image Quality Evaluation of Sanda Sports Video Based on BP Neural Network Perception

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Kai Fan ◽  
Xiaoye Gu
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Evaluation Method ◽  
Video Image ◽  
Time Analysis ◽  
Sports Video ◽  
Real Time Analysis ◽  
Video Images ◽  
Motion Video

In the special sports camera, there are subframes. A lens is composed of multiple frames. It will be unclear if a frame is cut out. The definition of video screenshots lies in the quality of video. To get clear screenshots, we need to find clear video. The purpose of this paper is to analyze and evaluate the quality of sports video images. Through the semantic analysis and program design of video using computer language, the video images are matched with the data model constructed by research, and the real-time analysis of sports video images is formed, so as to achieve the real-time analysis effect of sports techniques and tactics. In view of the defects of rough image segmentation and high spatial distortion rate in current sports video image evaluation methods, this paper proposes a sports video image evaluation method based on BP neural network perception. The results show that the optimized algorithm can overcome the slow convergence of weights of traditional algorithm and the oscillation in error convergence of variable step size algorithm. The optimized algorithm will significantly reduce the learning error of neural network and the overall error of network quality classification and greatly improve the accuracy of evaluation. Sanda motion video image quality evaluation method based on BP (back propagation) neural network perception has high spatial accuracy, good noise iteration performance, and low spatial distortion rate, so it can accurately evaluate Sanda motion video image quality.

Otoendoscopes to Enhance Telemedicine During the COVID-19 Pandemic

2021 ◽  
pp. 000348942110518
Author(s):  
Evette A. Ronner ◽  
Matthew E. Stenerson ◽  
Nicole H. Goldschmidt ◽  
Divya A. Chari ◽  
Gillian R. Diercks ◽  
...  
Keyword(s):  
Image Quality ◽  
Tympanic Membrane ◽  
Training Module ◽  
Image Capture ◽  
Improve Image Quality ◽  
Training Tool ◽  
Before And After ◽  
Ear Effusion ◽  
At Home

Objectives: As telemedicine has become increasingly utilized during the COVID-19 pandemic, portable otoendoscopy offers a method to perform an ear examination at home. The objective of this pilot study was to assess the quality of otoendoscopic images obtained by non-medical individuals and to determine the effect of a simple training protocol on image quality. Methods: Non-medical participants were recruited and asked to capture images of the tympanic membrane before and after completion of a training module, as well as complete a survey about their experience using the otoendoscope. Images were de-identified, randomized, and evaluated by 6 otolaryngologists who were blinded as to whether training had been performed prior to the image capture. Images were rated using a 5-point Likert scale. Results: Completion of a training module resulted in a significantly higher percentage of tympanic membrane visible on otoendoscopic images, as well as increased physician confidence in identifying middle ear effusion/infection, cholesteatoma, and deferring an in-person otoscopy ( P < .0001). However, even with improved image quality, in most cases, physicians reported that they would not feel comfortable using the images to for diagnosis or to defer an in-person examination. Most participants reported that the otoendoscope was simple to use and that they would feel comfortable paying for the device. Conclusions: At-home otoendoscopes can offer a sufficient view of the tympanic membrane in select cases. The use of a simple training tool can significantly improve image quality, though often not enough to replace an in-person otoscopic exam.

Observability of Very Thick Specimen by Using Transmission Scanning Electron Microscope

1971 ◽  
Vol 29 ◽  
pp. 26-27
Author(s):  
K. Shibatomi ◽  
T. Yamanoto ◽  
H. Koike
Keyword(s):  
Electron Microscope ◽  
Image Quality ◽  
Scanning Electron Microscope ◽  
Chromatic Aberration ◽  
Image Contrast ◽  
Objective Lens ◽  
Thick Specimen ◽  
Transmission Electron ◽  
Scanning Electron

In the observation of a thick specimen by means of a transmission electron microscope, the intensity of electrons passing through the objective lens aperture is greatly reduced. So that the image is almost invisible. In addition to this fact, it have been reported that a chromatic aberration causes the deterioration of the image contrast rather than that of the resolution. The scanning electron microscope is, however, capable of electrically amplifying the signal of the decreasing intensity, and also free from a chromatic aberration so that the deterioration of the image contrast due to the aberration can be prevented. The electrical improvement of the image quality can be carried out by using the fascionating features of the SEM, that is, the amplification of a weak in-put signal forming the image and the descriminating action of the heigh level signal of the background. This paper reports some of the experimental results about the thickness dependence of the observability and quality of the image in the case of the transmission SEM.

Organ doses and subjective image quality of indirect digital panoramic radiography

2001 ◽  
Vol 30 (6) ◽  
pp. 308-313 ◽  
Author(s):  
F Gijbels ◽  
G Sanderink ◽  
C Bou Serhal ◽  
H Pauwels ◽  
R Jacobs
Keyword(s):  
Image Quality ◽  
Panoramic Radiography ◽  
Organ Doses ◽  
Subjective Image Quality ◽  
Digital Panoramic Radiography

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

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