Quasi dynamic Huffman hardware encoder and encoding method

Abstract

The invention discloses a quasi dynamic Huffman hardware encoder and an encoding method; the encoder receives 2n BCD code data each time for encoding, wherein n is a positive integer; the encoder comprises a ranking network module, a tree building module, a tree parsing module, a cascade FIFO, and an output module; the ranking network module and the cascade FIFO are respectively connected with a 4-bit data input port, a start signal port, a clock port and a low level reset port; the ranking network module, the tree building module, the tree parsing module and the output module are connected in sequence; the cascade FIFO is connected with the output module; the output module is provided with a n+1-bit data output port, a n+1-bit data valid port, a data output start signal port and a data output end signal port. The design result shows that when a Nexys4 DDR platform is used, the encoder can work at a frequency above 100MHz; the encoder is high in throughput, low in delay, high in coding efficiency, and simple in structure.

Description

technical field [0001] The invention relates to the technical field of encoding and decoding, in particular to a quasi-dynamic Huffman hardware encoder and an encoding method. Background technique [0002] Huffman coding is a lossless data compression coding invented by David.A.Huffman in 1952. Thanks to its high efficiency, Huffman coding has been widely adopted in the fields of computer, data encryption and communication. The general Huffman coding method is generally implemented by looking up a static table or dynamically. The former is less flexible, and the latter is also dynamic when decoding data, which makes the software and hardware configuration of the receiving end equally complicated. The core process of Huffman coding is sorting, and sorting is a relatively complex and frequent operation for general-purpose CPUs. For Huffman coding with high speed and high real-time performance, the software sorting process has been difficult to meet. In contrast, the sorting...

AI Technical Summary

Problems solved by technology

The general Huffman coding method is generally implemented by looking up a static table or dynamically. The former is less flexible, while the latter is also dynamic when decoding data, which makes the software and hardware composition of the receiving end equally complicated.

The core process of Huffman coding is sorting, and sorting is a relatively complex and frequent operation for general-purpose CPUs

For fast and high real-time Huffman coding, the software sorting process has been difficult to meet

In contrast, the sorting circuit implemented by hardware can relatively reduce power consumption while ensuring the operation speed, and at the same time free the general-purpose CPU to deal with more complex problems, which is a better strategy.

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