What You Will Learn!
- Learn the applications of digital image representation, recognition, and compression
- Study image enhancement techniques such as equalization, level adjustment, contrast, and edge detection
- Explain the operation of lowpass, median, and edge detection filters
- Understand the use of the discrete cosine transform (DCT) in image compression
- Review the essential components of the JPEG standard and JPEG AI
Description
Digital image processing (DIP) has become indispensable in many disciplines, including electronics, computer, communications, and biomedical engineering. DIP forms the workhorse of media processing systems, allowing the streaming and storage of high-quality video. Following an introduction to DIP, participants will learn how digital images can be represented, recognized, and converted to various formats (RGB, grayscale, YUV) for efficient processing. The key image enhancement techniques will then be explained, including equalization, level adjustment, and contrast, as well as the use of lowpass, median, and edge detection filters. The discrete cosine transform (DCT) is widely used in image compression. The third section of the course discusses the DCT and compares its performance with the discrete Fourier transform (DFT). The final section of the course focuses on JPEG color image compression, JPEG AI, and MPEG motion video compression. It will briefly discuss the optimization between coded bit rate and image distortion, the role of deep learning, and the Adam algorithm. References for further reading are also provided. This concise course is geared toward anyone who is interested in the fundamental techniques used in the rapidly expanding field of DIP. Using 60 illustrative slides, a practical understanding is developed through many numeric design examples and demonstrations.
Who Should Attend!
- The course is beneficial for anyone who is interested in the rapidly expanding field of digital image processing