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Computational Imaging for Scene Understanding : Transient, Spectral, and Polarimetric Analysis
| Computational Imaging for Scene Understanding : Transient, Spectral, and Polarimetric Analysis |
| Autore | Funatomi Takuya |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (341 pages) |
| Disciplina | 006.6 |
| Altri autori (Persone) | OkabeTakahiro |
| Collana | Image. Sensors and image processing |
| Soggetto topico | Image processing - Digital techniques - Mathematics |
| ISBN |
1-394-28443-8
1-394-28441-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Introduction -- Part 1. Transient Imaging and Processing -- Chapter 1. Transient Imaging -- 1.1. Introduction -- 1.2. Mathematical formulation -- 1.2.1. Analysis of transient light transport propagation -- 1.2.2. Sparsity of the impulse response function T (x, t) -- 1.3. Capturing light in flight -- 1.3.1. Single-photon avalanche diodes (SPAD) -- 1.4. Applications -- 1.4.1. Range imaging -- 1.4.2. Material estimationand classification -- 1.4.3. Light transport decomposition -- 1.5. Non-line-of-sight imaging -- 1.5.1. Backprojection -- 1.5.2. Confocal NLOS and the light-cone transform -- 1.5.3. Surface-based methods -- 1.5.4. Virtualwaves and phasorfields -- 1.5.5. Discussion -- 1.6. Conclusion -- 1.7. References -- Chapter 2. Transient Convolutional Imaging -- 2.1. Introduction -- 2.2. Time-of-flight imaging -- 2.2.1. Correlationimage sensors -- 2.2.2. Convolutional ToF depth imaging -- 2.2.3. Multi-path interference -- 2.3. Transient convolutional imaging -- 2.3.1. Global convolutional transport -- 2.3.2. Transient imaging using correlation image sensors -- 2.3.3. Spatio-temporal modulation -- 2.4. Transient imagingin scatteringmedia -- 2.5. Present andfuturedirections -- 2.6. References -- Chapter 3. Time-of-Flight and Transient Rendering -- 3.1. Introduction -- 3.2. Mathematical modeling -- 3.2.1. Mathematical modeling for time-of-flight cameras -- 3.3. How to render time-of-flight cameras? -- 3.3.1. Challenges and solutions in time-of-flight rendering -- 3.4. Open-sourceimplementations -- 3.5. Applicationsof transient rendering -- 3.6. Future directions -- 3.7. References -- Part 2. Spectral Imaging and Processing -- Chapter 4. Hyperspectral Imaging -- 4.1. Introduction -- 4.2. 2D (raster scanning) architectures -- 4.2.1. Czerny-Turner grating spectrometers.
4.2.2. Transmission grating/prism spectrometers -- 4.2.3. Coded aperture spectrometers -- 4.2.4. Echelle spectrometers -- 4.3. 1D scanning architectures -- 4.3.1. Dispersive spectrometers -- 4.3.2. Interferometric methods -- 4.3.3. Interferometric filter methods -- 4.3.4. Polarization-based filter methods -- 4.3.5. Active illumination methods -- 4.4. Snapshot architectures -- 4.4.1. Bowen-Walravenimage slicer -- 4.4.2. Image slicing and imagemapping -- 4.4.3. Integral field spectrometry with coherent fiber bundles (IFS-F) -- 4.4.4. Integral field spectroscopy with lenslet arrays (IFS-L) -- 4.4.5. Filter array camera (FAC) -- 4.4.6. Computed tomography imaging spectrometry (CTIS) -- 4.4.7. Coded aperture snapshot spectral imager (CASSI) -- 4.5. Comparisonof snapshot techniques -- 4.5.1. The disadvantagesof snapshot -- 4.6. Conclusion -- 4.7. References -- Chapter 5. Spectral Modeling and Separation of Reflective-Fluorescent Scenes -- 5.1. Introduction -- 5.2. RelatedWork -- 5.3. Separation of reflection and fluorescence -- 5.3.1. Reflection and fluorescence models -- 5.3.2. Separation using high-frequency illumination -- 5.3.3. Discussion on the illumination frequency -- 5.3.4. Error analysis -- 5.4. Estimating the absorption spectra -- 5.5. Experiment results and analysis -- 5.5.1. Experimental setup -- 5.5.2. Quantitative evaluation of recovered spectra -- 5.5.3. Visual separation and relighting results -- 5.5.4. Separation by using high-frequency filters -- 5.5.5. Ambient illumination -- 5.6. Limitations and conclusion -- 5.7. References -- Chapter 6. Shape from Water -- 6.1. Introduction -- 6.2. Related works -- 6.3. Light absorption in water -- 6.4. Bispectral light absorption for depth recovery -- 6.4.1. Bispectral depth imaging -- 6.4.2. Depth accuracy and surface reflectance -- 6.5. Practical shape from water. 6.5.1. Non-collinear/perpendicular light-camera configuration -- 6.5.2. Perspective camera with a point source -- 6.5.3. Non-ideal narrow-band filters -- 6.6. Co-axial bispectral imaging system and experiment results -- 6.6.1. System configuration and calibration -- 6.6.2. Depth and shape accuracy -- 6.6.3. Complex static and dynamic objects -- 6.7. Trispectral light absorption for depth recovery -- 6.7.1. Trispectral depth imaging -- 6.7.2. Evaluation on the reflectance spectra database -- 6.8. Discussions -- 6.9. Conclusion -- 6.10. References -- Chapter 7. Far Infrared Light Transport Decomposition and Its Application for Thermal Photometric Stereo -- 7.1. Introduction -- 7.1.1. Contributions -- 7.2. Related work -- 7.2.1. Light transport decomposition -- 7.2.2. Computational thermal imaging -- 7.2.3. Photometric stereo -- 7.3. Far infrared light transport -- 7.4. Decomposition and application -- 7.4.1. Far infrared light transport decomposition -- 7.4.2. Separating the ambient component -- 7.4.3. Separating reflection and radiation -- 7.4.4. Separating diffuse and global radiations -- 7.4.5. Other options -- 7.4.6. Thermal photometric stereo -- 7.5. Experiments -- 7.5.1. Decomposition result -- 7.5.2. Surface normal estimation -- 7.6. Conclusion -- 7.7. References -- Chapter 8. Synthetic Wavelength Imaging: Utilizing Spectral Correlations for High-Precision Time-of-Flight Sensing -- 8.1. Introduction -- 8.2. Synthetic wavelength imaging -- 8.3. Synthetic wavelength interferometry -- 8.4. Synthetic wavelength holography -- 8.4.1. Imaging around corners with synthetic wavelength holography -- 8.4.2. Imaging through scattering media with synthetic wavelength holography -- 8.4.3. Discussion and comparison with the state of the art -- 8.5. Fundamental performance limits of synthetic wavelength imaging -- 8.6. Conclusion and future directions. 8.7. Acknowledgment -- 8.8. References -- Part 3. Polarimetric Imaging and Processing -- Chapter 9. Polarization-Based Shape Estimation -- 9.1. Fundamental theory of polarization -- 9.2. Reflection component separation -- 9.3. Phase angle of polarization -- 9.4. Surface normal estimation from the phase angle -- 9.5. Degree of polarization -- 9.6. Surface normal estimation from the degree of polarization -- 9.7. Stokes vector -- 9.8. Surface normal estimation from the Stokes vector -- 9.9. References -- Chapter 10. Shape from Polarization and Shading -- 10.1. Introduction -- 10.2. Related works -- 10.2.1. Shading and polarization fusion -- 10.2.2. Shape estimation under uncalibrated light sources -- 10.3. Problem setting and assumptions -- 10.4. Shading stereoscopic constraint -- 10.5. Polarization stereoscopic constraint -- 10.6. Normal estimation with two constraints -- 10.6.1. Algorithm 1: Recovering individual surface points -- 10.6.2. Algorithm 2: Recovering shape and light directions -- 10.7. Experiments -- 10.7.1. Simulation experiments with weights for two constraints -- 10.7.2. Real-world experiments -- 10.8. Conclusion and future works -- 10.9. References -- Chapter 11. Polarization Imaging in the Wild Beyond the Unpolarized World Assumption -- 11.1. Introduction -- 11.2. Mueller calculus -- 11.3. Polarizing filters -- 11.3.1. Linear polarizers -- 11.3.2. Reflectors -- 11.4. Polarization imaging -- 11.5. Image formation model -- 11.5.1. Partially linearly polarized incident illumination -- 11.5.2. Unpolarized incident illumination -- 11.5.3. Discussion -- 11.6. Polarization imaging reflectometry in the wild -- 11.7. Digital Single-Lens Reflex (DSLR) setup -- 11.7.1. Data acquisition -- 11.7.2. Calibration -- 11.7.3. Polarization processing pipeline -- 11.8. Reflectance recovery -- 11.8.1. Surface normal estimation. 11.8.2. Diffuse albedo estimation -- 11.8.3. Specular component estimation -- 11.9. Results and analysis -- 11.9.1. Results -- 11.9.2. Discussion and error analysis -- 11.10. References -- Chapter 12. Multispectral Polarization Filter Array -- 12.1. Introduction -- 12.2. Multispectral polarization filter array with a photonic crystal -- 12.3. Generalization of imaging and demosaicking with multispectral -- 12.4. Demonstration -- 12.5. Conclusion -- 12.6. References -- List of Authors -- Index -- EULA. |
| Record Nr. | UNINA-9910877776003321 |
Funatomi Takuya
|
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Digital geometry in image processing / / Jayanta Mukhopadhyay. [et al.]
| Digital geometry in image processing / / Jayanta Mukhopadhyay. [et al.] |
| Autore | Mukhopadhyaya Jayanta |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton, Fla. : , : Taylor & Francis, , 2013 |
| Descrizione fisica | 1 online resource (316 p.) |
| Disciplina | 006.601/516 |
| Collana | IIT kharagpur research monograph series |
| Soggetto topico |
Image processing - Digital techniques - Mathematics
Geometry - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN |
0-429-08675-X
1-4665-0568-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover; Contents; Series Preface; Preface; List of Figures; List of Tables; Symbol Description; Chapter 1 Digital Topology: Fundamentals; Chapter 2 Distance Functions in Digital Geometry; Chapter 3 Digitization of Straight Lines and Planes; Chapter 4 Digital Straightness and Polygonal Approximation; Chapter 5 Parametric Curve Estimation and Reconstruction; Chapter 6 Medial Axis Transform; Chapter 7 Modeling of a Voxelated Surface; References; Color Insert; Back Cover |
| Record Nr. | UNINA-9910463156603321 |
|
Mukhopadhyaya Jayanta
|
||
| Boca Raton, Fla. : , : Taylor & Francis, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Digital geometry in image processing / / Jayanta Mukhopadhyay. [et al.]
| Digital geometry in image processing / / Jayanta Mukhopadhyay. [et al.] |
| Autore | Mukhopadhyaya Jayanta |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton, Fla. : , : Taylor & Francis, , 2013 |
| Descrizione fisica | 1 online resource (316 p.) |
| Disciplina | 006.601/516 |
| Collana | IIT kharagpur research monograph series |
| Soggetto topico |
Image processing - Digital techniques - Mathematics
Geometry - Data processing |
| ISBN |
0-429-08675-X
1-4665-0568-0 |
| Classificazione | COM012000MAT003000TEC015000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover; Contents; Series Preface; Preface; List of Figures; List of Tables; Symbol Description; Chapter 1 Digital Topology: Fundamentals; Chapter 2 Distance Functions in Digital Geometry; Chapter 3 Digitization of Straight Lines and Planes; Chapter 4 Digital Straightness and Polygonal Approximation; Chapter 5 Parametric Curve Estimation and Reconstruction; Chapter 6 Medial Axis Transform; Chapter 7 Modeling of a Voxelated Surface; References; Color Insert; Back Cover |
| Record Nr. | UNINA-9910786733103321 |
|
Mukhopadhyaya Jayanta
|
||
| Boca Raton, Fla. : , : Taylor & Francis, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Math Physics Foundation of Advanced Remote Sensing Digital Image Processing / / Lei Yan [and three others]
| Math Physics Foundation of Advanced Remote Sensing Digital Image Processing / / Lei Yan [and three others] |
| Autore | Yan Lei <1956-> |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (XXVI, 490 p. 321 illus., 60 illus. in color.) |
| Disciplina | 006.6 |
| Soggetto topico |
Image processing - Digital techniques - Mathematics
Remote sensing - Mathematics |
| ISBN | 981-9917-78-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Remote Sensing Digital Image Processing Technology I -- Overview of Remote Sensing Digital Image Processing -- System Support Conditions of Remote Sensing Digital Image Processing and Analysis -- Mathematical Basis for the Overall Processing and Analysis of Remote Sensing Digital Images -- The Physical Foundation and Global Analysis of Remote Sensing Digital Images -- Remote Sensing Digital Image Processing Technology II -- Remote Sensing Digital Image Pixel Processing Theory I: Linear System with Space–Time Domain Convolution -- Basic Theory of Remote Sensing Digital Image Pixel Processing II: Time–Frequency Fourier Transform from Convolution to Multiplication -- Remote Sensing Digital Image Pixel Processing Theory III: Frequency Domain Filtering -- Remote Sensing Digital Image Pixel Processing Theory IV: Time Domain Sampling -- Basics of Remote Sensing Digital Image Pixel Transformation I: Space–Time Equivalent Orthogonal Basis -- Basis of Remote Sensing Digital Image Pixel Transformation II: Time–Frequency Orthogonal Basis -- Remote Sensing Digital Image Processing Technology Ⅲ -- Remote Sensing Digital Image Processing: Noise Reduction and Image Reconstruction -- Digital Image Compression -- Pattern recognition (image segmentation) -- Pattern recognition (feature extraction and classification) -- Applications of Remote Sensing Digital Image Processing IV: Color Transform and 3D Reconstruction -- Applications of Remote Sensing Digital Image Processing. |
| Record Nr. | UNINA-9910736027103321 |
|
Yan Lei <1956->
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| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Sampling theory in signal and image processing : an international journal
| Sampling theory in signal and image processing : an international journal |
| Pubbl/distr/stampa | Potsdam, New York, : Sampling Publishing, 2002- |
| Descrizione fisica | 1 online resource |
| Disciplina | 612 |
| Soggetto topico |
Signal processing - Digital techniques - Mathematics
Image processing - Digital techniques - Mathematics Engineering - Statistical methods Sampling (Statistics) Traitement du signal - Techniques numériques - Mathématiques Traitement d'images - Techniques numériques - Mathématiques Ingénierie - Méthodes statistiques Échantillonnage (Statistique) Proceso digital de señales - Matemáticas Proceso digital de imágenes - Matemáticas Ingeniería - Métodos estadísticos Muestreo (Estadística) |
| Soggetto genere / forma |
Periodical
periodicals. Periodicals Periodicals. Périodiques. |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | STSIP |
| Record Nr. | UNISA-996213835403316 |
| Potsdam, New York, : Sampling Publishing, 2002- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Sampling theory, signal processing, and data analysis
| Sampling theory, signal processing, and data analysis |
| Pubbl/distr/stampa | Basel : , : Birkhäuser, , 2021- |
| Descrizione fisica | 1 online resource |
| Disciplina | 510 |
| Soggetto topico |
Signal processing - Digital techniques - Mathematics
Image processing - Digital techniques - Mathematics Sampling (Statistics) Engineering - Statistical methods Traitement du signal - Techniques numériques - Mathématiques Traitement d'images - Techniques numériques - Mathématiques Échantillonnage (Statistique) Ingénierie - Méthodes statistiques |
| Soggetto genere / forma | Periodicals. |
| ISSN | 2730-5724 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910547300403321 |
| Basel : , : Birkhäuser, , 2021- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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