Application of Varint_LZW encoding algorithm in image compression

The rapid development of information technology has brought tremendous pressure to data transmission and compression, so data compression has great significance. Data compression before transmission can reduce transmission bandwidth, and data compression before storage can reduce data storage. The Lempel-Ziv-Welch (LZW) coding process has a very high requirement on the bit width of the data cached in the dictionary in RAM for such images with the same color appearing continuously. LZW is used to encode the same 16-bit pixel data continuously. When the data is encoded to 128 pixels, the 128bit wide RAM will be filled up. If the same data is continued to be encoded, the RAM will overflow the data. In this paper, Varint encoding algorithm is introduced to solve this problem, and Varint encoding is carried out before LZW encoding. Varint has good compression effect on high continuous and repeated data. Therefore, for this type of data, Varint_LZW encoding shows lower utilization rate of RAM bit width than LZW encoding.

I. Background and Introduction

With the development of the Internet, the demand for data transmission, processing, and storage has shown explosive growth. It is extremely important to improve transmission speed and processing speed. On the other hand, it is important to ensure that no information is lost. Reducing the amount of data transmission also has great research significance, among which data compression technology has important application significance for the latter. In terms of data compression, various compression schemes have been proposed, such as LZW- HuffMAM^[l], which can effectively improve the bandwidth of high bandwidth mobile interfaces (MIHBS) in sensor networks by 52%. Another example is the comparison of the newly proposed LZ77 and Deflate algorithms of ePLZ77_Varint^[2], and the compression rate and time are improved.