Cargando…
DIBR-Synthesized Image Quality Assessment With Texture and Depth Information
Accurately predicting the quality of depth-image-based-rendering (DIBR) synthesized images is of great significance in promoting DIBR techniques. Recently, many DIBR-synthesized image quality assessment (IQA) algorithms have been proposed to quantify the distortion that existed in texture images. Ho...
Autores principales: | Wang, Guangcheng, Shi, Quan, Shao, Yeqin, Tang, Lijuan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8597928/ https://www.ncbi.nlm.nih.gov/pubmed/34803593 http://dx.doi.org/10.3389/fnins.2021.761610 |
Ejemplares similares
-
Deep Learning-Based Synthesized View Quality Enhancement with DIBR Distortion Mask Prediction Using Synthetic Images
por: Zhang, Huan, et al.
Publicado: (2022) -
Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties
por: Jacobs, Richard H. A. H., et al.
Publicado: (2016) -
Introducing Depth Information Into Generative Target Tracking
por: Sun, Dongyue, et al.
Publicado: (2021) -
Adaptive Bilateral Texture Filter for Image Smoothing
por: Xu, Huiqin, et al.
Publicado: (2022) -
Image Recognition of Pediatric Pneumonia Based on Fusion of Texture Features and Depth Features
por: Wang, Hao-Nan, et al.
Publicado: (2022)