We will also look at the details of how, to obtain the prediction coefficients, when linear predictions are formed. While now it's best quantified and then entropy encoded. In that case, however, the prediction order was encoded, error-free or losslessly. We will spend a bit more time on predictive coding and, more specifically, with the so-called DPCM, differential pulse code modulation. Although, on their own, they do not achieve competitive results, as compared to the state of the antagons of standards, such as JPEG, on one hand, they demonstrate means of achieving compression, but they're also typically parts. We covered in this segment some of the simpler image compression techniques. In all cases, example images and videos pertaining to specific application domains will be utilized. Emphasis on the special role sparsity plays in modern image and video processing will also be given. We will introduce and use a wide variety of such tools – from optimization toolboxes to statistical techniques. In this class not only will you learn the theory behind fundamental processing tasks including image/video enhancement, recovery, and compression - but you will also learn how to perform these key processing tasks in practice using state-of-the-art techniques and tools. We will provide a mathematical framework to describe and analyze images and videos as two- and three-dimensional signals in the spatial, spatio-temporal, and frequency domains. This course will cover the fundamentals of image and video processing. Some important examples of image and video processing include the removal of degradations images suffer during acquisition (e.g., removing blur from a picture of a fast moving car), and the compression and transmission of images and videos (if you watch videos online, or share photos via a social media website, you use this everyday!), for economical storage and efficient transmission. Digital image and video processing continues to enable the multimedia technology revolution we are experiencing today. The ability to process image and video signals is therefore an incredibly important skill to master for engineering/science students, software developers, and practicing scientists. Moreover they come in a wide range of the electromagnetic spectrum - from visible light and infrared to gamma rays and beyond. In this class you will learn the basic principles and tools used to process images and videos, and how to apply them in solving practical problems of commercial and scientific interests.ĭigital images and videos are everywhere these days – in thousands of scientific (e.g., astronomical, bio-medical), consumer, industrial, and artistic applications.
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