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.
4.7
(130 ratings)
13,876 already enrolled
Instructors:
English
Tiếng Việt
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
T. C. Chang Professor of Computer Science
Shree K. Nayar is the T. C. Chang Professor of Computer Science at Columbia University, where he leads the Columbia Vision Laboratory (CAVE). His laboratory specializes in developing cutting-edge computational imaging and computer vision systems. Nayar’s research focuses on three primary areas: the creation of innovative cameras that offer new types of visual information, the design of physics-based models for vision and graphics, and the development of algorithms aimed at understanding and interpreting scenes from images.Professor Nayar’s work is highly interdisciplinary, bridging the domains of imaging, computer vision, robotics, virtual and augmented reality, visual communication, computer graphics, and human-computer interaction. His pioneering research has significant real-world applications in these fields, advancing both the technology and our understanding of visual systems.In addition to his research, Nayar is an educator, teaching several advanced courses at Columbia University, including 3D Reconstruction - Multiple Viewpoints, 3D Reconstruction - Single Viewpoint, Camera and Imaging, Features and Boundaries, and Visual Perception. These courses reflect his expertise in computer vision and imaging technologies and contribute to shaping the next generation of researchers and engineers in these fields.
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4.7 course rating
130 ratings
Frequently asked questions
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