Camera and Imaging
Master digital imaging principles, camera operations, and processing techniques to capture and enhance high-quality images with professional-level results.
Master digital imaging principles, camera operations, and processing techniques to capture and enhance high-quality images with professional-level results.
This comprehensive course explores the fundamental principles of imaging and camera systems. Students learn how cameras work, including lens systems, image sensors, and color sensing. The course covers advanced topics like HDR imaging, binary image processing, and Fourier transforms. Through detailed study of image formation, sensing, and processing, students gain both theoretical knowledge and practical skills in digital imaging technology.
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What you'll learn
Understand camera optics and image formation
Master image sensor characteristics
Implement HDR imaging techniques
Process binary images effectively
Apply image filtering methods
Analyze images using Fourier transforms
Skills you'll gain
This course includes:
6.5 Hours PreRecorded video
30 assignments
Access on Desktop
FullTime access
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There are 6 modules in this course
This comprehensive course covers the fundamentals of imaging technology and camera systems. The curriculum progresses from basic principles of image formation and lens systems to advanced topics in image processing. Students learn about sensor technologies, color imaging, HDR techniques, and various image processing methods including convolution and Fourier transforms.
Getting Started: Camera and Imaging
Module 1 · 2 Hours to complete
Image Formation
Module 2 · 3 Hours to complete
Image Sensing
Module 3 · 4 Hours to complete
Binary Images
Module 4 · 2 Hours to complete
Image Processing I
Module 5 · 3 Hours to complete
Image Processing II
Module 6 · 3 Hours to complete
Fee Structure
Instructor
Pioneer in Computational Imaging and Professor at Columbia University
Dr. Shree K. Nayar is the T. C. Chang Professor of Computer Science at Columbia University, where he leads the Columbia Vision Laboratory (CAVE). His research focuses on computational imaging and computer vision, with key interests in developing novel camera systems, physics-based models for vision and graphics, and algorithms for scene understanding from images. Dr. Nayar's work has significant applications across various fields, including robotics, virtual reality, augmented reality, and human-computer interfaces.He holds a B.E. in Electrical Engineering from the Birla Institute of Technology, an M.S. in Electrical and Computer Engineering from North Carolina State University, and a Ph.D. from Carnegie Mellon University. Throughout his career, Dr. Nayar has received numerous accolades for his contributions to the field, including the 2010 ACM Software Systems Award for his work on the GroupLens Recommender System. He has published over 300 scientific papers and holds more than 80 patents related to imaging technologies.Dr. Nayar teaches several courses on Coursera, including "3D Reconstruction - Multiple Viewpoints" and "Camera and Imaging," aimed at providing students with foundational knowledge in computer vision and imaging systems.
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