VLSI image compression encoder based on wavelet transformation

Abstract

A VLSI image compression encoder based on wavelet transformation comprises a center control, a data exchange unit, a wavelet transformation driver with one to three level, a two-dimensional wavelet transformation engine, a combined encoder and two data bufferings of RAM_A and RAM_B; firstly, the encoder carries out three level wavelet transformation on an input image by using the wavelet transformation driver with one to three level and the two-dimensional wavelet transformation engine; and then an optimum quantizer in the combined encoder respectively quantizes each subband; entropy coding is carried out on the quantized coefficient by a self-adapting zero run-length encoder and an Exp-Golomb encoder in the combined encoder; and finally the compression code stream is obtained. In the encoder, hardware is used for realizing an image compression algorithm and improving image compression speed, and causes that an image recorder has real time image compression capability, thus effectively prolonging recording time and improving transmission capability.

Description

technical field [0001] The invention relates to an image compression encoder based on hardware, in particular to a high-performance and low-complexity VLSI image compression encoder based on wavelet transform. Background technique [0002] With the popularity of computer technology applications, digital images have become the main image information carrier that people come into contact with every day. Images have the characteristics of large amount of information and large amount of data. According to analysis, less than 20% of the information received by human beings is received through sound, while more than 80% of the information received through eyes has been recorded since ancient times. Seeing is better than smelling” vividly illustrates the importance and urgency of image information exchange. However, general images are high-dimensional data. As the size increases, the amount of data increases at a geometric rate. If the contradiction between the huge amount of data...

AI Technical Summary

Problems solved by technology

However, the current image compression algorithms generally have high computational complexity. For example, the JPEG2000 algorithm uses complex EBCOT encoding and the PCRD-OPT code rate allocation algorithm that needs to be solved iteratively. When it is implemented by a general-purpose processor or a programmable DSP, Difficult to achieve high-speed real-time image compression coding

However, the JPEG algorithm with low computational complexity uses 8×8 image blocks for independent encoding, which will cause serious block effects at higher compression ratios, greatly reducing image quality.

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