A blind stereoscopic image quality evaluator with segmented stacked autoencoders considering the whole visual perception route

A blind stereoscopic image quality evaluator with segmented stacked autoencoders considering the whole visual perception route

Most of the current blind stereoscopic image quality assessment (SIQA) algorithms cannot show reliable accuracy. One reason is that they do not have the deep architectures and the other reason is that they are designed on the relatively weak biological basis, compared with findings on human visual s...

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Bibliographic Details
Main Authors: Jiachen Yang, Kyohoon Sim, Xinbo Gao, Wen Lu, Qinggang Meng, Baihua Li
Format: Default Article
Published: 2018
Subjects:
Artificial intelligence not elsewhere classified
Other information and computing sciences not elsewhere classified
Stereoscopic image quality assessment
Retinal ganglion cell
Lateral geniculate nucleus
Segmented stacked autoencoders
Edge quality
Color quality
Artificial Intelligence and Image Processing
Information and Computing Sciences not elsewhere classified
Online Access:https://hdl.handle.net/2134/35682
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https://hdl.handle.net/2134/35682

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