Image Statistics in Visual Computing
Auteurs : Pouli Tania, Reinhard Erik, Cunningham Douglas W.
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.
BACKGROUND: Introduction. The Human Visual System. Image Collection and Calibration. IMAGE STATISTICS: First Order Statistics. Gradients, Edges, and Contrast. Fourier Analysis. Dimensionality Reduction. Wavelet Analysis. Markov Random Fields. BEYOND TWO DIMENSIONS: Color. Depth Statistics. Time and Motion. Appendix. Bibliography.
Date de parution : 12-2013
15.2x22.9 cm
Thèmes d’Image Statistics in Visual Computing :
Mots-clés :
Human Visual System; Natural Image Statistics; statistics of natural images; Receptive Fields; relation of natural image statistics to human vision; Westonbirt Arboretum; statistical regularities and patterns in visual data; Image Patches; natural image statistics applied to visual computing; HDR; image databases suitable for statistics; HDR Image; statistical transforms and human perception; Markov Random Fields; statistical regularities in computer vision; computer graphics; and image processing; Independent Component Analysis; Center Surround Processing; Image Ensemble; Power Spectrum; Spatial Frequency; Spectral Slope; Natural Images; Phase Spectrum; Image Denoising; Optical Flow; Temporal Integration Window; Haar Wavelets; Wavelet Coefficients; Color Space; Complex Wavelets; Color Transfer; CIE XYZ