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Image processing and data analysis the multiscale approach

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  • "For graduate students and researchers already experienced in image processing and data analysis, a guide to a wide range of powerful and innovative data-analysis techniques."
  • "1. The wavelet transform; 1.1 Multiscale methods; 1.2 The continuous wavelet transform; 1.3 Examples of wavelet functions; 1.4 The discrete wavelet transform/ 1.5 Multiresolution based on the median transform/ 1.6 Multiresolution and mathematical morphology; 2. Multiresolution support and filtering; 2.1 Noise modeling; 2.2 Multiresolution support; 2.3 Filtering; 2.4 Image comparison using a multiresolution quality criterion; 3. Deconvolution; 3.1 Introduction to deconvolution; Regularization using the multiresolution support; 3.3 Multiscale entropy and image restoration; 3.4 Image restoration for aperture synthesis; 4. 1D signals and euclidean data analysis; 4.1 Analysis of 1D signals: spectral analysis; 4.2 Wedding the wavelet transform and multivariate data analysis; 4.3 The kohonean self-organizing map in wavelet space; 4.4 Multiresolution regression and forecastin; 5. Geometric registration; 5.1 Image distortions; 5.2 Geometrical image registration; 5.3 Ground control points; 5.4 Image registration using the wavelet transform; 5.5 Application; 5.6 Error analysis; 5.7 Conclusion on multscale goemetric registration; 6. Disparity analysis in remote sensing; 6.1 Definitions; 6.2 Disparity mapping; 6.3 Disparity mapping with the wavelet transform; 6.4 Image registration; 6.5 Application to real images; 6.6 Conclusion on disparity analysis. 7. Image compression; 7.1 Pyramidal median transform and image compression; 7.2 Examples and assessments; 7.3 Image transmission over networks; 7.4 Conclusion on image compression; 8. Object detection and point clustering; 8.1 The problem and the data; 8.2 Pyramidal median transform and minkowski operators; 8.3 Conclusion on astronomical object detection; 8.4 Object detection and clustering in point patterns; 8.5 Conclusion: cluster analysis in constant time; 9. Multiscale vision models; 9.1 Artificial vision and astronomical images; 9.2 Object definition in wavelet transform space; Partial reconstruction; Applications to a real image; 9.5 Vision models and image classes; Appendix A. Variance stabilization; A.1 Mean and variance expansions; A.2 Deterination of centered moments; A.3 Study of the expansions for the variance; A.4 Variance-stabilizing transformation; Appendix B. Software information; Appendix C. Acronys.; Bibliography; Index."

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  • "Electronic books"@en
  • "Matériel didactique"

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  • "Image processing and data analysis the multiscale approach"
  • "Image processing and data analysis the multiscale approach"@en
  • "Image processing and data analysis : the multiscale approach"
  • "Image Processing and Data Analysis The Multiscale Approach"
  • "Image Processing and Data Analysis : the Multiscale Approach"@en

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