Neural Image Compression Lecture
Nowadays, digital images and video are everywhere. Image Processing revolutionizes very many domains, notably:
-Digital Media (video/image/movie) Content Production and Broadcasting, Social Media Analytics,
-Medical/Biological/Dental Imaging and Diagnosis,
-Big Visual Data Analytics,
-Internet and Communications (media broadcasting, streaming).
-Scientific Imaging of any sort, e.g., Remote Sensing, Environment Sensing.
Photoshop and many other image processing tools are ubiquitous.
Furthermore, Image Processing is typically the first step that enables diverse applications, in unison with Computer Vision and Machine Learning:
-Autonomous Systems (cars, drones, vessels) Perception,
-Robotics Perception and Control,
-Intelligent Human-Machine Interaction,
-Anthropocentric (human-centered) Computing,
-Smart Cities/Buildings and Assisted living.
This lecture overviews Neural Image Compression that has many applications in image storage and communications. It covers the following topics in detail: Image Compression Types, Image Compression Evaluation, Transform Image Compression, Neural Predictive Image Coding, Neural Image Autoencoding, CNN-Transformer Image Compression, RNN Image Compression, Variable Rate RNN Image Compression.