Digital Image Processing and Compression

About this course

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, edge detection, and color 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 and color JPEG compression code 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 over 80 illustrative slides, a practical understanding is developed through many numeric design examples and demonstrations. It also contains a short quiz.Learning OutcomesLearn the applications of digital image representation, recognition, and compressionStudy image enhancement techniques such as equalization, level adjustment, contrast, and edge detectionExplain the operation of lowpass, median, and edge detection filtersUnderstand the use of the discrete cosine transform (DCT) in image compressionReview the essential components of the JPEG standard and JPEG AIAbout t