NDLI: Hybrid deep emperor penguin classifier algorithm-based image quality assessment for visualisation application in HDR environments

Content Provider	IET Digital Library
Author	Tade, Sunil L. Vyas, Vibha
Abstract	One of the main open challenges in visualisation applications such as cathode ray tube (CRT) monitor, liquid-crystal display (LCD), and organic light-emitting diode (OLED) display is the robustness for high dynamic range (HDR) environs. This is due to the imperfections in the sensor and the incapability to track interest points successfully because of the brightness constancy in visualisation applications. To address this problem, different tone mapping operators are required for visualising HDR images on standard displays. However, these standard displays have different dynamic ranges. Thus, there is a need for a new model to find the best quality tone mapped image for specific kinds of visualisation applications. The authors propose a hybrid deep emperor penguin classifier to accurately classify the tone mapped images for different visualisation applications. Here, a selective deep neural network is trained to predict the quality of a tone-mapped image. Based on this quality, a decision is made as to the suitability of the image for CRT monitor, LCD display or OLED display. Also, they evaluate the proposed model on the TMIQD database and the simulation results prove that the proposed model outperforms the state-of-the-art image quality assessment methods.
Starting Page	2579
Ending Page	2587
Page Count	9
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 11, Sep (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.1371
Journal	IET Image Processing
Publisher Date	2020-04-29
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Brightness Cathode Ray Tube Cathode Ray Tube Monitor Computer Displays Computer Vision And Image Processing Technique Different Dynamic Ranges Different Tone Mapping Operators Different Visualisation Application Display Technology Graphics Technique HDR Environments High Dynamic Range Environs Hybrid Deep Emperor Penguin Classifier Algorithm-based Image Quality Assessment Image Colour Analysis Image Processing LCD Display Light Emitting Diode Lighting Liquid Crystal Displays Liquid-crystal Display Neural Computing Technique Neural Nets OLED Display Optical, Image And Video Signal Processing Organic Light Emitting Diode Organic Light-emitting Diode Quality Tone Mapped Image Standard Displays State-of-the-art Image Quality Assessment Method Statistics Television Displays Tone-mapped Image Visualisation Application Visualising HDR Image
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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