This chapter provides an introductory overview of image and video coding. We explore the transition from continuous real-world scenes to discrete digital images, and present the basic knowledge of image and video signal processing. Color images can be decomposed into RGB componentsRGB components, illustrating how they contribute to the color intensity. The YUV video data formatYUV video data format is also discussed, as well as its advantages over RGB for transmitting image and video signals. There are various YUV sampling techniquesYUV sampling techniques, such as 4:4:4, 4:2:2, and 4:2:0, in order to balance the visual quality fidelity and the data storage efficiency. In the realm of AI-based Image and video codingimage and video coding, the importance of diverse and high quality datasets for training and evaluating compression algorithms is undoubted. There are several typical image and video datasets, with unique characteristics and applications in compression. Lastly, the necessity of compression is analyzed in modern digital ecosystems, advocating for AI-driven compression techniquesAI-driven compression techniques that surpass traditional methods in achieving higher rate distortion performance. The Quality assessmentquality assessment for compressed image and video data should include both the sides ofSubjective and objective assessmentssubjective and objective assessments.