- Email: [email protected]
Introduction to Image and Video Processing
Image and Video Processing 3.1
Basic Linear F i l t e r i n g w i t h Application to Image Enhancement Alan C. Bovik, and Scott T. Acton ..............................................................................................................................................
99
Introduction • Impulse Response, Linear Convolution, and Frequency Response • Linear Image E n h a n c e m e n t D i s c u s s i o n . References 3.2
Nonlinear Filtering for Image A n a l y s i s a n d E n h a n c e m e n t Gonzalo R. Arce, ]an Bacca, and ]osf L. Paredes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
109
Introduction • Weighted Median Smoothers and Filters • Image Noise Cleaning • Image Z o o m i n g • Image Sharpening • Edge Detection • Conclusion • References 3.3
M o r p h o l o g i c a l Filtering for Image Enhancement and Feature Detection Petros Maragos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction • Morphologic Image Operators • Morphologic Filters for Image E n h a n c e m e n t Morphologic Operators for Template Matching • Morphologic Operators for Feature Detection O p t i m a l Design of Morphologic Filters for E n h a n c e m e n t • Conclusions • References
135
3.4
Wavelet Denoising for Image Enhancement
Dong Wei, Umesh Rajashekar, and Alan C. Bovik .................
157
Introduction • Wavelet Shrinkage Denoising • Image E n h a n c e m e n t via Wavelet Shrinkage Examples • Image Denoising Using Natural Scene Statistics • S u m m a r y • References 3.5
Basic Methods for Image Restoration and Identification Reginald L. Lagendijk and ]an Biemond . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
167
Introduction • Blur Models • Image Restoration Algorithms • Blur Identification Algorithms • References
W. Clem Karl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction • Direct Regularization Methods • Iterative Regularization Methods • Regularization Parameter Choice • S u m m a r y " References
3.6
Regularization in Image Restoration and Reconstruction
183
3.7
Multichannel Image Recovery Nikolas P. Galatsanos, Miles N. Wernick, Aggelos K. Katsaggelos, and Rafael Molina .......................................................................................................
203
Introduction • Imaging Model • Multichannel Image Estimation Approaches • Explicit Multichannel Recovery Approaches • Implicit Approach to Multichannel Image Recovery • Acknowledgments • References
3.8
Multi-Frame Image Restoration
Timothy J. Schulz .........................................................................................
219
Introduction • Mathematic Models • The Multi-Frame Restoration Problem • Nuisance Parameters and Blind Restoration • Applications • Acknowledgments • References
3.9
Iterative Image Restoration
Aggelos K. Katsaggelos, and Chun-Jen Tsai .......................................................
235
Introduction • Iterative Recovery Algorithms • Spatially Invariant Degradation • Matrix-Vector Formulation • Use of Constraints • Additional Considerations • Discussion • References 3.10
Motion Detection and Estimation
]anusz Konrad ............................................................................................
253
Introduction • Notation and Preliminaries • Motion Detection • M o t i o n Estimation • Practical Motion Estimation Algorithms • Perspectives • Acknowledgments • References 3.11
Video Enhancement and Restoration Reginald L. Lagendijk, Peter M.B. van Roosmalen, Jan Biemond, Andrei Rare¢, and Marcel ]. T. Reinders .................................................................................... Introduction • Spatio-Temporal Noise Filtering • Blotch Detection and Removal • Vinegar Syndrome Removal • Intensity Flicker Correction • Kinescope Moir6 Removal • Concluding Remarks • References
275
3.12
Local a n d G l o b a l S t e r e o M e t h o d s Yang Liu and ].K. Aggarwal ...................................................................... Introduction • Background of Computational Stereo Vision • A Taxonomy of Stereo Correspondence Algorithms • Conclusion • Acknowledgment • References
3.13
Image S e q u e n c e
Stabilization, Mosaicking, and Superresolution Rama Chellappa, S. Srinivasan, G. Aggarwal, and A. Veeraraghavan .................................................................................................................
Introduction • Biologic Motivation: Insect Navigation • Global Motion Models • Algorithm two-dimensional Stabilization • Mosaicking • Motion Superresolution • three-dimensional Stabilization • S u m m a r y . References
297
309
Basic Linear F i l t e r i n g w i t h Application to Image Enhancement Alan C. Bovik, and Scott T. Acton ..............................................................................................................................................
99
Introduction • Impulse Response, Linear Convolution, and Frequency Response • Linear Image E n h a n c e m e n t D i s c u s s i o n . References 3.2
Nonlinear Filtering for Image A n a l y s i s a n d E n h a n c e m e n t Gonzalo R. Arce, ]an Bacca, and ]osf L. Paredes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
109
Introduction • Weighted Median Smoothers and Filters • Image Noise Cleaning • Image Z o o m i n g • Image Sharpening • Edge Detection • Conclusion • References 3.3
M o r p h o l o g i c a l Filtering for Image Enhancement and Feature Detection Petros Maragos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction • Morphologic Image Operators • Morphologic Filters for Image E n h a n c e m e n t Morphologic Operators for Template Matching • Morphologic Operators for Feature Detection O p t i m a l Design of Morphologic Filters for E n h a n c e m e n t • Conclusions • References
135
3.4
Wavelet Denoising for Image Enhancement
Dong Wei, Umesh Rajashekar, and Alan C. Bovik .................
157
Introduction • Wavelet Shrinkage Denoising • Image E n h a n c e m e n t via Wavelet Shrinkage Examples • Image Denoising Using Natural Scene Statistics • S u m m a r y • References 3.5
Basic Methods for Image Restoration and Identification Reginald L. Lagendijk and ]an Biemond . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
167
Introduction • Blur Models • Image Restoration Algorithms • Blur Identification Algorithms • References
W. Clem Karl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction • Direct Regularization Methods • Iterative Regularization Methods • Regularization Parameter Choice • S u m m a r y " References
3.6
Regularization in Image Restoration and Reconstruction
183
3.7
Multichannel Image Recovery Nikolas P. Galatsanos, Miles N. Wernick, Aggelos K. Katsaggelos, and Rafael Molina .......................................................................................................
203
Introduction • Imaging Model • Multichannel Image Estimation Approaches • Explicit Multichannel Recovery Approaches • Implicit Approach to Multichannel Image Recovery • Acknowledgments • References
3.8
Multi-Frame Image Restoration
Timothy J. Schulz .........................................................................................
219
Introduction • Mathematic Models • The Multi-Frame Restoration Problem • Nuisance Parameters and Blind Restoration • Applications • Acknowledgments • References
3.9
Iterative Image Restoration
Aggelos K. Katsaggelos, and Chun-Jen Tsai .......................................................
235
Introduction • Iterative Recovery Algorithms • Spatially Invariant Degradation • Matrix-Vector Formulation • Use of Constraints • Additional Considerations • Discussion • References 3.10
Motion Detection and Estimation
]anusz Konrad ............................................................................................
253
Introduction • Notation and Preliminaries • Motion Detection • M o t i o n Estimation • Practical Motion Estimation Algorithms • Perspectives • Acknowledgments • References 3.11
Video Enhancement and Restoration Reginald L. Lagendijk, Peter M.B. van Roosmalen, Jan Biemond, Andrei Rare¢, and Marcel ]. T. Reinders .................................................................................... Introduction • Spatio-Temporal Noise Filtering • Blotch Detection and Removal • Vinegar Syndrome Removal • Intensity Flicker Correction • Kinescope Moir6 Removal • Concluding Remarks • References
275
3.12
Local a n d G l o b a l S t e r e o M e t h o d s Yang Liu and ].K. Aggarwal ...................................................................... Introduction • Background of Computational Stereo Vision • A Taxonomy of Stereo Correspondence Algorithms • Conclusion • Acknowledgment • References
3.13
Image S e q u e n c e
Stabilization, Mosaicking, and Superresolution Rama Chellappa, S. Srinivasan, G. Aggarwal, and A. Veeraraghavan .................................................................................................................
Introduction • Biologic Motivation: Insect Navigation • Global Motion Models • Algorithm two-dimensional Stabilization • Mosaicking • Motion Superresolution • three-dimensional Stabilization • S u m m a r y . References
297
309