Image Processing and Computer Vision eBooks

1 Digital picture compression and coding structure 3
2 Fundamentals of human vision and vision modeling 45
3 Coding artifacts and visual distortions 87
4 Video quality testing 125
5 Perceptual video quality metrics - a review 155
6 Philosophy of picture quality scale 181
7 Structural similarity based image quality assessment 225
8 Vision model based digital video impairment metrics 243
9 Computational models for just-noticeable difference 281
10 No-reference quality metric for degraded and enhanced video 305
11 Video quality experts group 325
12 HVS based perceptual video encoders 337
13 Perceptual image coding 361
14 Foveated image and video coding 431
15 Artifact reduction by post-processing in image compression 459
16 Reduction of color bleeding in DCT block-coded video 489
17 Error resilience for video coding service 503
18 Critical issues and challenges 543
A VQM performance metrics 575

Product Description:
This volume, and the accompanying CD-ROM, contain 163 contributions from ICCVG04, which is one of the main international conferences in computer vision and computer graphics in Central Europe. This biennial conference was organised in 2004 jointly by the Association for Image Processing, the Polish-Japanese Institute of Information Technology, and the Silesian University of Technology

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Book Description:
The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system.

In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models