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Point cloud lossless compression method based on classification rearrangement

A lossless compression and rearrangement technology, applied in image communication, digital video signal modification, stereo system, etc., can solve the problem of insufficient compression rate, achieve high compression rate, increase spatial correlation, and achieve the effect of lossless data

Pending Publication Date: 2022-05-27
FUZHOU UNIV +1
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Problems solved by technology

However, the current lossless compression coding generally has the problem that the compression rate is not high enough.

Method used

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  • Point cloud lossless compression method based on classification rearrangement
  • Point cloud lossless compression method based on classification rearrangement
  • Point cloud lossless compression method based on classification rearrangement

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Embodiment Construction

[0023] The technical solutions of the present invention will be described in detail below with reference to the accompanying drawings.

[0024] like Figure 1-3 As shown, a method for lossless compression of point cloud depth images based on classification and rearrangement of the present invention includes the following steps:

[0025] 1) The encoding process is as follows figure 1 The coding flow chart is as follows:

[0026] Step S1, determine a threshold. The pixels in the image are divided into several categories, so that the gray values ​​of the pixels in the same category are similar. Firstly, the threshold is determined adaptively according to the histogram of the image, so that the two types of pixels are close in number. Let the histogram of the original image be: H={C(g)|C(g)∈[0, S 2 ] and C(g)∈Z, g=0,1,...,65536};. Then the threshold G that should be selected is G=argmin T {|∑ g＜T C(g)-∑ h≥T C(h)|}, where g, T, and h are the values ​​of the histogram, and ...

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Abstract

The invention relates to a point cloud lossless compression method based on classification rearrangement. The method comprises the following steps of: firstly, determining a threshold: dividing pixels in an image into a plurality of categories, and enabling gray values of the pixels in the same category to be close to each other; according to the determined threshold value, C1, C2 and a pixel mask map Mp are obtained through classification; the Mp is a binary pixel mask image, and the size of the Mp is SxS; the Mp records category information of all pixels, but the Mp occupies a large number of bits, and the Mp is further partitioned and merged to obtain a partitioned mask image Mb; all the pixels of the whole image can be arranged into a one-dimensional sequence D by traversing the partitioned mask image and the pixels according to the sequence of a third-order Hilbert curve, and the sequence D is divided into two subsequences D1 and D2 which correspond to a high gray value and a low gray value respectively; and coding the data streams D1 and D2 and the block mask pattern Mb by adopting JPEG-LS, then forming two paths of coded bit streams, and finally outputting the two paths of coded bit streams. According to the method, the dual requirements of data lossless and high compression rate can be met.

Description

technical field [0001] The invention relates to image compression coding technology, in particular to a point cloud lossless compression method based on classification and rearrangement. Background technique [0002] With the development of 3D sensing and capture technologies, 3D lidar point cloud technologies have demonstrated their utility in digital perception of real-world environments, such as virtual / augmented / mixed reality (AR / VR / MR), moving maps, Historic scanning, smart cities, robotics and autonomous driving. The point cloud data has massive data, which is a huge challenge to the storage and transmission of computer equipment information, and its effective compression is one of the indispensable steps. [0003] According to whether there is information loss in the coding process, image coding can be divided into lossy compression coding and lossless compression coding. Although lossy compression coding can compress the data to a great extent, due to the loss of i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N13/161H04N13/106H04N19/182H04N19/176
CPCH04N13/161H04N13/106H04N19/182H04N19/176
Inventor 郑明魁黄施平王泽峰王适陈建
Owner FUZHOU UNIV
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