Data Compression: Unlocking Efficiency in Computer Vision with Data Compression

In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder.

How you will benefit

(I) Insights, and validations about the following topics:

Chapter 1: Data compression

Chapter 2: Audio file format

Chapter 3: Codec

Chapter 4: JPEG

Chapter 5: Lossy compression

Chapter 6: Lossless compression

Chapter 7: Image compression

Chapter 8: Transform coding

Chapter 9: Video codec

Chapter 10: Discrete cosine transform

(II) Answering the public top questions about data compression.

(III) Real world examples for the usage of data compression in many fields.

Who this book is for

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Data Compression.