Image Quality Assessment of Computer generated Images Based on Machine Learning 4nd Soft Computing

Release: Image.Quality.Assessment.of.Computer.generated.Images.Based.on.Machine.Learning.4nd.Soft.Computing

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Image Quality Assessment of Computer-generated Images: Based on Machine Learning 4nd Soft Computing

Image Quality Assessment of Computer-generated Images: Based on Machine Learning 4nd Soft Computing By André Big4nd
English | PDF,EPUB | 2018 | 96 Pages | ISBN : 331973542X | 8.17 MB
Image Quality Assessment is well-known f08r measuring the perceived image degradation of natural scene images but is still an emerging topic f08r computer-generated images. This book addresses this problem 4nd presents recent advances based on soft computing. It is aimed at students, practitioners 4nd researchers in the field of image processing 4nd related areas such as computer graphics 4nd visualization.
In this book, we first clarify the differences between natural scene images 4nd computer-generated images, 4nd address the problem of Image Quality Assessment (IQA) by focusing on the visual perception of noise. Rather than using known perceptual models, we first investigate the use of soft computing approaches, classically used in Artificial Intelligence, as full-reference 4nd reduced-reference metrics. Thus, by creating Learning Machines, such as SVMs 4nd RVMs, we can assess the perceptual quality of a computer-generated image. We also investigate the use of interval-valued fuzzy 5euts as a no-reference metric.
These approaches are treated both the08retically 4nd practically, f08r the complete process of IQA. The learning step is perf08rmed using a database built from experiments with human users 4nd the resulting models can be used f08r any image computed with a stochastic rendering alg08rithm. This can be useful f08r detecting the visual convergence of the different parts of an image during the rendering process, 4nd thus to optimize the computation. These models can also be extended to other applications that h4ndle complex models, in the fields of signal processing 4nd image processing.
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