High-speed real-time processing arithmetic coding method based on JPEG 2000 standard

Abstract

The invention discloses a high-speed real-time processing arithmetic coding method based on a JPEG 2000 standard, which mainly solves the problem of the traditional coding method that the complexity is high and the coding speed is low. The coding process comprises the following steps of: judging the types of double context symbol pairs, respectively predicting the probability interval values according to the types and calculating the coding parameter; updating the code values, judging the current normalization type and normalizing the code values; if no new context symbol is input, emptying the code values; caching the code streams upon normalization and emptying process according to the byte and class; and finally, outputting the classified cached code streams in turn according to the priority order. The invention has the advantages of high coding speed and low complexity, and is applicable to the image compression coding of various high-speed digital apparatuses, in particular to the high-speed real-time satellite remote sensing image coding.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to compression coding, in particular to an arithmetic entropy coding method involving high-speed real-time processing, which is used for image compression coding of various digital devices, especially high-speed real-time satellite image compression coding. Background technique [0002] With the development of multimedia and network technology and its application in medical imaging, remote sensing images and digital image / video transmission, the existing still image compression standard JPEG can no longer meet the requirements of current practical applications. In November 2000, a new still image compression standard JPEG2000 was established. One of the core technologies of this standard is to use the arithmetic entropy coding method to encode the data after wavelet transformation, so as to realize the compression processing of image data. [0003] The basic coding process of...

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Problems solved by technology

[0009] The fourth is the arithmetic given in the article "A Dual-Symbol Coding Arithmetic Coder Architecture Design for High Speed ​​EBCOTCoding Engine in JPEG2000" published by Xu Chao at the 2005 Int.Conf.Image Process. (ICIP'05) International Conference Entropy coding method, which can achieve a single clock to process 2 context symbol pairs when different contexts are input, but when the same context is input, the encoding structure cannot process simultaneously

Although this method can realize the parallel processing of double-context symbol pairs, but the method requires more storage bits, which causes certain difficulties in chip design, and the implementation complexity is too high

[0011] The sixth is the article "VLSI implementation of a high-speed MQ encoder suitable for JPEG2000" published by some domestic scholars such as Hua Lin and others in the journal "Research and Progress in Solid State Electronics" in 2003 (Volume 23, 2003 , No. 4, pp. 421-426), the arithmetic entropy coding method given in this method adopts dynamic pipeline technology, and the processing speed is 0.625 context symbol pairs processed by a single clock, and the coding speed is low

[0012] The seventh is the article "VLSI Design of a High-Speed ​​and Area-Efficient JPEG2000 Encoder" published by Mei Kuizhi et al. in the IEEE Trans.on Circuits and System for VideoTechnology journal in 2007 (Volume 17, No. , pp. 1065-1078) gives the arithmetic entropy coding method, which uses multi-input synchronous pipeline technology to realize arithmetic entropy coding, and the processing speed is 0.625 context symbol pairs processed by a single clock, and the coding speed is low

[0013] The above seven high-speed arithmetic entropy coding hardware implementation methods have the following defects: if the implementation complexity is low, the processing speed is also low, such as methods six and seven; if the processing speed is increased, the implementation complexity increases sharply, such as method one to five

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