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Image processing and analysis : a primer

Author: Georgiĭ Lʹvovich Gimelʹfarb; Patrice Delmas
Publisher: London ; Hackensack, NJ : World Scientific Publishing Europe Ltd., [2019]
Series: Primers in electronics and computer science, v. 3.
Edition/Format:   Print book : EnglishView all editions and formats
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Document Type: Book
All Authors / Contributors: Georgiĭ Lʹvovich Gimelʹfarb; Patrice Delmas
ISBN: 9781786345813 1786345811
OCLC Number: 1035268101
Description: xvi, 229 pages ; 24 cm.
Contents: Note continued: 2.4.Questions and exercises --
3.Filtering to Denoise or Enhance --
3.1.Modelling image noise --
3.2.Moving window transform (MWT) --
3.3.Linear filtering --
3.3.1.Mean filter --
3.3.2.Fast box filtering --
3.3.3.Gaussian filter --
3.4.Nonlinear filtering --
3.4.1.Median filter --
3.4.2.Rank filtering --
3.5.Questions and exercises --
4.Filtering to Segment --
4.1.Measuring segmentation accuracy --
4.2.Modelling image regions --
4.3.Histogram thresholding --
4.3.1.Adaptive object-background thresholding --
4.3.2.Gaussian mixture model --
4.3.3.Unimodal thresholding --
4.4.Colour segmentation --
4.4.1.RGB-HSI colour representations --
4.4.2.Colour thresholding --
4.4.3.Multi-region segmentation --
4.5.Labelling connected regions --
4.6.Questions and exercises --
5.Morphological Filtering --
5.1.Binary morphology --
5.1.1.Structuring element --
5.1.2.Erosion --
5.1.3.Dilation --
5.1.4.Opening --
5.1.5.Closing --
5.1.6.Hit-and-miss transform Note continued: 5.2.Greyscale morphology --
5.2.1.Erosion --
5.2.2.Dilation --
5.2.3.Opening and closing --
5.2.4.Top-hat and dual top-hat transforms --
5.3.Questions and exercises --
6.Deforming Boundaries to Segment --
6.1.Evolving an AC --
6.1.1.Parametric ACs --
6.1.2.Geometric (level-set) ACs --
6.2.Active shape models --
6.2.1.Derivation of the PDM --
6.2.2.Registration of training images --
6.2.3.Using PCA to determine a PDM --
6.2.4.Matching an ASM to an unseen image --
6.3.Questions and exercises --
7.Filtering to Find Points-of-Interest --
7.1.Differential image properties: Gradients and Hessians --
7.1.1.Gradients and Hessians in a digital image --
7.1.2.DoG, DoOG, and LoG --
7.1.3.Inverse USAN areas --
7.2.Edge detection --
7.2.1.Thresholding gradients --
7.2.2.Canny edge detector --
7.3.Detecting POIs --
7.3.1.Rotation-invariant POIs --
7.3.2.Scale-rotation invariance: SIFT and SURF --
7.4.Questions and exercises --
8.Transforming Image Plane Note continued: 8.1.Signal interpolation for restoring continuous images --
8.2.Basic geometric transformations --
8.2.1.Forward and backward coordinate mapping --
8.2.2.Affine transformations --
8.2.3.Polynomial warping --
8.3.Questions and exercises --
9.Spectra and Spectral Filtering --
9.1.ID complex exponentials --
9.2.2D/3D exponentials --
9.3.Discrete Fourier transform (DFT) --
9.3.1.Amplitude, phase, and power spectra --
9.3.2.Some properties of the DFT --
9.3.3.Discrete cosine transform (DCT) --
9.3.4.Fast Fourier transform (FFT) --
9.4.Wavelets and wavelet decompositions --
9.4.1.Multi-resolution analysis (MRA) --
9.4.2.Haar wavelets --
9.4.3.Smooth wavelets --
9.5.Filtering in the spectral domain --
9.5.1.Convolution in the spectral domain --
9.5.2.Low-, high-, and band-pass spectral filtering --
9.5.3.Inverse and Wiener filters --
9.5.4.Homomorphic and cepstral filters --
9.6.Questions and exercises --
Appendix A Further Reading --
A.1.More diverse sources Note continued: A.2.Bibliographical and historical notes --
Appendix B Symbols and Math Notation --
B.1.Latin symbols --
B.2.Greek symbols --
B.3.Math notation --
Appendix C Abbreviations.
Series Title: Primers in electronics and computer science, v. 3.
Responsibility: Georgy Gimelʹfarb, Patrice Delmas.

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