ABSTRACT
This chapter discusses the necessity for image and video compression. It shows that image and video compression become enabling techniques in exploding number of digital multimedia applications. The chapter also shows that the feasibility of image and video compression rests in redundancy removal. It explains three types of redundancy: statistical redundancy, coding redundancy, and psychovisual redundancy. The chapter argues that the term information is considered one of the fundamental concepts in image and video compression. It addresses some information theory results. The chapter considers measure of information and the entropy of an information source. Entropy is a very important concept in information theory and communications. The chapter introduces some coding theorems, which play a fundamental role in studying image and video compression. The visual quality of reconstructed image and video is a crucial criterion in the evaluation of the performance of visual transmission or storage systems.
