Natural Image Statistics

A Probabilistic Approach to Early Computational Vision

Authors:

ISBN: 978-1-84882-490-4 (Print) 978-1-84882-491-1 (Online)

Table of contents (21 chapters)

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  1. Front Matter

    Pages i-xix

  2. Introduction

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      Book Chapter

      Pages 1-21

      Introduction

  3. Background

    1. Front Matter

      Pages 23-23

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      Book Chapter

      Pages 25-49

      Linear Filters and Frequency Analysis

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      Book Chapter

      Pages 51-66

      Outline of the Visual System

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      Book Chapter

      Pages 67-90

      Multivariate Probability and Statistics

  4. Statistics of Linear Features

    1. Front Matter

      Pages 91-91

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      Book Chapter

      Pages 93-130

      Principal Components and Whitening

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      Book Chapter

      Pages 131-150

      Sparse Coding and Simple Cells

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      Book Chapter

      Pages 151-175

      Independent Component Analysis

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      Book Chapter

      Pages 177-196

      Information-Theoretic Interpretations

  5. Nonlinear Features and Dependency of Linear Features

    1. Front Matter

      Pages 197-197

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      Book Chapter

      Pages 199-211

      Energy Correlation of Linear Features and Normalization

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      Book Chapter

      Pages 213-237

      Energy Detectors and Complex Cells

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      Book Chapter

      Pages 239-261

      Energy Correlations and Topographic Organization

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      Book Chapter

      Pages 263-276

      Dependencies of Energy Detectors: Beyond V1

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      Book Chapter

      Pages 277-293

      Overcomplete and Non-negative Models

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      Book Chapter

      Pages 295-306

      Lateral Interactions and Feedback

  6. Time, Color, and Stereo

    1. Front Matter

      Pages 307-307

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      Book Chapter

      Pages 309-323

      Color and Stereo Images

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      Book Chapter

      Pages 325-361

      Temporal Sequences of Natural Images

  7. Conclusion

    1. Front Matter

      Pages 363-363

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      Book Chapter

      Pages 365-374

      Conclusion and Future Prospects

  8. Appendix: Supplementary Mathematical Tools

    1. Front Matter

      Pages 375-375

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      Book Chapter

      Pages 377-397

      Optimization Theory and Algorithms

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      Book Chapter

      Pages 399-405

      Crash Course on Linear Algebra

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      Book Chapter

      Pages 407-418

      The Discrete Fourier Transform

  9. Back Matter

    Pages 427-451

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