Data Compression

ref:data compression complete reference managing compression introduction of data compression

Introduction

• This is the process of converting an input data stream (source / original raw data) into another data stream (output / bitstream / compressed) that has a smaller size.
• a stream is either a file or buffer in memory
• Data compression aims to counter
  • inevatability of storage overflow
  • eliminate wait time of data transfers
• Also known as source coding.
• source can either be memoryless or it can have memory.
• All data compression techniques are based on the same principle, i.e remove redundancy form original data.
• Any non-random data has some structure that can be exploited to achieve a smaller representation of the data, where no structure is discernable.
• General law
  • assing short codes to common events and long codes to rare events
• The redundancies in data depend on the type of data(text, images, sound ) which is why a new compression method has to be developed for a specific type of data and it performs best on this type of data.
• No such thing as a universal, efficient data compression algorithm.
• What is the SP theory?(simplicity and power)
• Broad categories of data compression
  • Run Length Encoding
  • Statistical methods
  • Dictionary-based methods
  • Transforms