Lossless compression of hyperspectral images using backward search in context window

GAO Fang; LIU Yu; GUO Shu-xu

doi:10.3788/OPE.20152308.2376

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Lossless compression of hyperspectral images using backward search in context window

更新时间：2020-08-12

- Lossless compression of hyperspectral images using backward search in context window
- Optics and Precision Engineering Vol. 23, Issue 8, Pages: 2376-2383(2015)
- 作者机构：
  
  吉林大学电子科学与工程学院,吉林长春 130012
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152308.2376
  CLC： TP751.1
- Received：11 May 2015，
  
  Revised：03 June 2015，
  
  Published：25 August 2015
- 稿件说明：
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高放, 刘宇, 郭树旭. 基于上下文窗口中反向搜索的高光谱图像无损压缩[J]. 光学精密工程, 2015,23(8): 2376-2383

GAO Fang, LIU Yu, GUO Shu-xu. Lossless compression of hyperspectral images using backward search in context window[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2376-2383
高放, 刘宇, 郭树旭. 基于上下文窗口中反向搜索的高光谱图像无损压缩[J]. 光学精密工程, 2015,23(8): 2376-2383 DOI： 10.3788/OPE.20152308.2376.

GAO Fang, LIU Yu, GUO Shu-xu. Lossless compression of hyperspectral images using backward search in context window[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2376-2383 DOI： 10.3788/OPE.20152308.2376.

摘要

针对基于单波段预测的高光谱图像无损压缩压缩比低的问题

提出基于上下文窗口中反向搜索的高光谱图像无损压缩算法。首先

对待测像素设定上下文窗口

计算其预测参考值并进行反向搜索预测得到待测像素的候选预测值。然后

选取与预测参考值最接近的候选预测值作为待测像素的最终预测结果。最后

对预测残差图像进行一阶算术编码完成压缩过程。利用提出的算法对AVIRIS 1997高光谱图像进行了实验

结果显示

提出的算法通过对上下文窗口、等效系数和有效像素阈值的优化取值

使反向搜索预测的效果达到最好

经过算术编码器编码后

可以得到一个3.63倍的平均压缩比。该方法具有较低的算法复杂度和内存需求

优于当前已报道的基于单波段预测的其他各种高光谱图像无损压缩算法。

Abstract

An efficient lossless compression scheme of hyperspectral images based on one-band-prediction was proposed by using backward search in a context window to improve the compression ratio of the hyperspectral images. Firstly

the context window for a pixel to be tested was defined and the prediction reference value under testing was calculated. Then

the candidate predictors which were mostly closed to the prediction reference value were selected as the final prediction results of the pixel to be measured. Finally

the predicted residual image was coded by a first-order arithmetic to implement the image compression. The method proposed was used in the experiments on hyperspectral images from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) 1997

and the results show that the method has obtained the best prediction results of backward search by optimizing the context window

equivalent coefficients and effective pixel thresholds. After coding by an arithmetic coder

the average compression ratio is 3.63。The method has a lower computing complexity and smaller memory requirements

and outperforms all other lossless compression schemes for hyperspectral images that have been previously reported.

关键词

Keywords

references

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