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Part I
Basis for Compression and Communication
This part provides a basis for our advanced research on visual data compression
and communication both theoretically and technically.
Chapter 1 discusses Shannon’s information theory, which is the theoretical basis
for visual data compression and communication. First, we introduce the concept of
entropy, which is the minimum length for lossless compression of a source, accord-
ing to Shannon’s source coding theorem. Huffman coding and arithmetic coding are
taken as examples to explain what source coding is and how a source is compressed
toward its entropy. The rate distortion theorem is also discussed because of its im-
portance to guiding the lossy compression of a source. Second, we introduce ...