Image Statistics in Visual Computing

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A01=Douglas W. Cunningham
A01=Erik Reinhard
A01=Tania Pouli
advanced visual computing techniques
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Author_Douglas W. Cunningham
Author_Erik Reinhard
Author_Tania Pouli
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Category1=Non-Fiction
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Category=JMB
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Center Surround Processing
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Color Space
Color Transfer
colour processing
Complex Wavelets
computational neuroscience
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Haar Wavelets
HDR
HDR Image
high
human
Human Visual System
Image Denoising
Image Ensemble
Image Patches
image perception
images
Independent Component Analysis
Language_English
Markov Random Fields
natural
Natural Image Statistics
Natural Images
Optical Flow
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Phase Spectrum
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range
receptive
Receptive Fields
regularities
softlaunch
Spatial Frequency
Spectral Slope
statistical
statistical learning methods
system
Temporal Integration Window
vision science
visual pattern analysis
Wavelet Coefficients
Westonbirt Arboretum

Product details

  • ISBN 9781568817255
  • Weight: 678g
  • Dimensions: 152 x 229mm
  • Publication Date: 13 Dec 2013
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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To achieve the complex task of interpreting what we see, our brains rely on statistical regularities and patterns in visual data. Knowledge of these regularities can also be considerably useful in visual computing disciplines, such as computer vision, computer graphics, and image processing. The field of natural image statistics studies the regularities to exploit their potential and better understand human vision. With numerous color figures throughout, Image Statistics in Visual Computing covers all aspects of natural image statistics, from data collection to analysis to applications in computer graphics, computational photography, image processing, and art.

The authors keep the material accessible, providing mathematical definitions where appropriate to help readers understand the transforms that highlight statistical regularities present in images. The book also describes patterns that arise once the images are transformed and gives examples of applications that have successfully used statistical regularities. Numerous references enable readers to easily look up more information about a specific concept or application. A supporting website also offers additional information, including descriptions of various image databases suitable for statistics.

Collecting state-of-the-art, interdisciplinary knowledge in one source, this book explores the relation of natural image statistics to human vision and shows how natural image statistics can be applied to visual computing. It encourages readers in both academic and industrial settings to develop novel insights and applications in all disciplines that relate to visual computing.

Tania Pouli, Erik Reinhard, Douglas W. Cunningham

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