Wesley E. Snyder is Professor Emeritus of Electrical and Computer Engineering at North Carolina State University. He was previously a professor at the Bowman Gray School of Medicine and worked at the GE Corporate Research and Development Center, NASA Langley Research Center, and the West German Air and Space Agency (DLR). He has published 179 research papers and was chosen as an Outstanding Engineering Educator in North Carolina in 1993. He was made fellow of the Institute of Electrical and Electronics Engineers (IEEE), Gladden Fellow (University of Western Australia), and Fellow of the American Institute of Medical and Biomedical Engineering. Hairong Qi is the Gonzalez Family Professor of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. Her research interests include collaborative signal and image processing, hyperspectral imaging, and bioinformatics. She is the recipient of a National Science Foundation CAREER Award, numerous best paper awards at international conferences, and was awarded the highest impact paper from the Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society in 2012.

• Part I. Preliminaries: 1. Computer vision, some definitions, and some history; 2. Writing programs to process images; 3. Review of mathematical principles; 4. Images – representation and creation; Part II. Preprocessing: 5. Kernel operators; 6. Noise removal; 7. Mathematical morphology; Part III. Image Understanding: 8. Segmentation; 9. Parametric transforms; 10. Representing and matching shape; 11. Representing and matching scenes; Part IV. The 2-D Image in a 3-D World: 12. Relating to three dimensions; 13. Developing computer vision algorithms.

'This new textbook by Snyder and Qi covers fundamental topics in computer vision. The authors do an outstanding job of discussing the subject. I like the way that required mathematical background is presented in the context of computer vision, thus reducing prerequisites on the part of the reader to basic calculus and introductory computer programming. The book is ideally suited for a first course in computer vision at the senior or first-year graduate level in a technical discipline, such as computer science, engineering, physics, or mathematics. I commend the authors for their style of presentation and for keeping a sharp focus on fundamentals.' Rafael C. Gonzalez, Distinguished-Service Professor Emeritus, Electrical Engineering and Computer Science, University of Tennessee

Wesley E. Snyder is Professor Emeritus of Electrical and Computer Engineering at North Carolina State University. He was previously a professor at the Bowman Gray School of Medicine and worked at the GE Corporate Research and Development Center, NASA Langley Research Center, and the West German Air and Space Agency (DLR). He has published 179 research papers and was chosen as an Outstanding Engineering Educator in North Carolina in 1993. He was made fellow of the Institute of Electrical and Electronics Engineers (IEEE), Gladden Fellow (University of Western Australia), and Fellow of the American Institute of Medical and Biomedical Engineering. Hairong Qi is the Gonzalez Family Professor of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. Her research interests include collaborative signal and image processing, hyperspectral imaging, and bioinformatics. She is the recipient of a National Science Foundation CAREER Award, numerous best paper awards at international conferences, and was awarded the highest impact paper from the Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society in 2012.

• Part I. Preliminaries: 1. Computer vision, some definitions, and some history; 2. Writing programs to process images; 3. Review of mathematical principles; 4. Images – representation and creation; Part II. Preprocessing: 5. Kernel operators; 6. Noise removal; 7. Mathematical morphology; Part III. Image Understanding: 8. Segmentation; 9. Parametric transforms; 10. Representing and matching shape; 11. Representing and matching scenes; Part IV. The 2-D Image in a 3-D World: 12. Relating to three dimensions; 13. Developing computer vision algorithms.

'This new textbook by Snyder and Qi covers fundamental topics in computer vision. The authors do an outstanding job of discussing the subject. I like the way that required mathematical background is presented in the context of computer vision, thus reducing prerequisites on the part of the reader to basic calculus and introductory computer programming. The book is ideally suited for a first course in computer vision at the senior or first-year graduate level in a technical discipline, such as computer science, engineering, physics, or mathematics. I commend the authors for their style of presentation and for keeping a sharp focus on fundamentals.' Rafael C. Gonzalez, Distinguished-Service Professor Emeritus, Electrical Engineering and Computer Science, University of Tennessee

Wesley E. Snyder is Professor Emeritus of Electrical and Computer Engineering at North Carolina State University. He was previously a professor at the Bowman Gray School of Medicine and worked at the GE Corporate Research and Development Center, NASA Langley Research Center, and the West German Air and Space Agency (DLR). He has published 179 research papers and was chosen as an Outstanding Engineering Educator in North Carolina in 1993. He was made fellow of the Institute of Electrical and Electronics Engineers (IEEE), Gladden Fellow (University of Western Australia), and Fellow of the American Institute of Medical and Biomedical Engineering. Hairong Qi is the Gonzalez Family Professor of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. Her research interests include collaborative signal and image processing, hyperspectral imaging, and bioinformatics. She is the recipient of a National Science Foundation CAREER Award, numerous best paper awards at international conferences, and was awarded the highest impact paper from the Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society in 2012.

• Part I. Preliminaries: 1. Computer vision, some definitions, and some history; 2. Writing programs to process images; 3. Review of mathematical principles; 4. Images – representation and creation; Part II. Preprocessing: 5. Kernel operators; 6. Noise removal; 7. Mathematical morphology; Part III. Image Understanding: 8. Segmentation; 9. Parametric transforms; 10. Representing and matching shape; 11. Representing and matching scenes; Part IV. The 2-D Image in a 3-D World: 12. Relating to three dimensions; 13. Developing computer vision algorithms.

'This new textbook by Snyder and Qi covers fundamental topics in computer vision. The authors do an outstanding job of discussing the subject. I like the way that required mathematical background is presented in the context of computer vision, thus reducing prerequisites on the part of the reader to basic calculus and introductory computer programming. The book is ideally suited for a first course in computer vision at the senior or first-year graduate level in a technical discipline, such as computer science, engineering, physics, or mathematics. I commend the authors for their style of presentation and for keeping a sharp focus on fundamentals.' Rafael C. Gonzalez, Distinguished-Service Professor Emeritus, Electrical Engineering and Computer Science, University of Tennessee