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Wavelet image compression method based on fast and successive approximation to quantification

A successive approximation and image compression technology, applied in image communication, television, electrical components, etc., can solve problems such as reducing memory requirements, reducing encoder performance, etc., to reduce encoding time, remove correlation, and improve performance.

Inactive Publication Date: 2008-02-27
ZTE CORP
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  • Application Information

AI Technical Summary

Problems solved by technology

In order to solve this problem, W.K.Lin and N.Burgress proposed the LZC (Listless zero codes) image compression method which is convenient for hardware implementation. The advantage of the LZC method over the SPIHT method is that it does not require a list in the process of encoding and decoding. Instead, it is Using two flag bitmaps to store tree information not only simplifies the original SPIHT method, but also greatly reduces memory requirements, but this compression method greatly reduces the performance of the encoder

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  • Wavelet image compression method based on fast and successive approximation to quantification
  • Wavelet image compression method based on fast and successive approximation to quantification

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Embodiment Construction

[0052] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0053] As shown in Figure 1: said wavelet image coder of the present invention is generally made of four parts:

[0054] The first part in the figure is the wavelet transform part. The present invention adopts 9 / 7 biorthogonal wavelet transform, decomposes 5 layers, and uses symmetric extension.

[0055] The second part is to quantize and encode the high-frequency sub-bands after wavelet transform. Here, the fast successive approximation quantization and improved embedded coding strategy are adopted. The following is a detailed introduction to its principle. In the previous successive approximation quantization process, for each successive approximation quantization process, an important map will be obtained by applying the current threshold value to all wavelet coefficients, and in the part of the important map In the band scan, all...

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Abstract

This invention discloses a compressing method for wavelet images based on approaching quantization one by one quickly including: analyzing an image to be processed to several sub-bands of different frequencies by wavelet transformation, carrying out modulating codes of difference pulse to a sub-band with the lowest frequency, coding difference amplitude and symbols after coding, carrying out quick approaching to quantization code one by one to HF sub-bands then to carry out entropy code to the sub-bands of HF and LF, which reduces relativity among symbols since the lowest band sub-band of LL occupying most energy of transformed coefficient is coded completely and an independent code technology to symbol separation.

Description

technical field [0001] The invention is an embedded zero-tree wavelet image compression method for still images, mainly based on fast successive approximation quantization and sign and amplitude separation coding techniques. Background technique [0002] With the advent of the information age, the amount of digital image data is quite large, and the mass storage, processing and transmission of image information has become one of the biggest problems in its hardware and software technology. Taking digital TV as an example, if it is a digital TV image in SIF (Source InputFormat) format, NTSC system, color, 4:4:4 sampling, then the amount of data per frame is 2028Kb, and the data flow per second can reach 60.8MB. A 650MB CD-ROM can only store 325 frames of images in total, and the playable program time is only 10.7 seconds. From this simple example, we can see how huge the amount of image information after digitization is. It is obviously unrealistic to simply expand the memo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N7/26H04N19/124H04N19/13H04N19/156H04N19/423H04N19/52H04N19/63H04N19/91
Inventor 刘利章王云峰薛宝林
Owner ZTE CORP
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