精确质量控制的遥感图像JPEG2000压缩方法

宋蓓蓓; 孙文方

doi:10.3788/OPE.20132108.2180

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精确质量控制的遥感图像JPEG2000压缩方法

信息科学 | 更新时间：2020-08-12

- 精确质量控制的遥感图像JPEG2000压缩方法
- JPEG2000 compression for remote sensing images with precise quality control
- 光学精密工程 2013年21卷第8期页码：2180-2186
- 作者机构：
  
  1. 长安大学信息工程学院,陕西西安,710064
  2. 中国空间技术研究院西安分院,陕西西安,710100
- 作者简介：
- 基金信息：
  
  大尺寸有障碍空间角度与基面位置测量的关键技术()
- DOI：10.3788/OPE.20132108.2180
  中图分类号： TP752
- 收稿日期：2013-01-29，
  
  修回日期：2013-03-19，
  
  网络出版日期：2013-08-20，
  
  纸质出版日期：2013-08-15
- 稿件说明：
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宋蓓蓓孙文方. 精确质量控制的遥感图像JPEG2000压缩方法[J]. 光学精密工程, 2013,21(8): 2180-2186

SONG Bei-bei SUN Wen-fang. JPEG2000 compression for remote sensing images with precise quality control[J]. Editorial Office of Optics and Precision Engineering, 2013,21(8): 2180-2186
宋蓓蓓孙文方. 精确质量控制的遥感图像JPEG2000压缩方法[J]. 光学精密工程, 2013,21(8): 2180-2186 DOI： 10.3788/OPE.20132108.2180.

SONG Bei-bei SUN Wen-fang. JPEG2000 compression for remote sensing images with precise quality control[J]. Editorial Office of Optics and Precision Engineering, 2013,21(8): 2180-2186 DOI： 10.3788/OPE.20132108.2180.

摘要

提出了一种精确控制图像压缩质量的遥感图像JPEG2000压缩方法。根据小波变换的完全重构和子带系数量化误差统计独立特性，建立了压缩图像峰值信噪比质量指标与小波系数编码量化误差的数学表达关系式。在传统JPEG2000率失真理论的基础上，建立以压缩图像质量为目标，最小化编码码率的模型，并给出了压缩图像质量控制的码流优化截取方法。对标准测试图像以及卫星遥感图像进行实验，并与传统JPEG2000方法进行比较。结果显示，该方法具有相同的编码架构和复杂度，能够精确控制压缩图像质量，控制精度小于1%。对于序列多幅遥感图像，在相同平均码率条件下，提出的方法具有更高的整体压缩图像峰值信噪比。

Abstract

A remote sensing image JPEG2000 compression scheme with precise quality control was proposed. According to the perfect reconstruction of wavelet filter banks and the statistical independence of subband coefficient quantization error

a mathematical expression formula was established to describe the relation between the peak signal to noise ratio and the wavelet coefficient quantization error. Based on the traditional JPEG2000 rate distortion model

a distortion-based rate minimization model was constructed and optimization truncation coding stream to obtain a desired target image compression quality was given. An experiment on standard test images and satellite remote sensing image was performed and obtained results were compared with that of the conventional rate-based distortion minimization JPEG2000 encoding. Results indicate that the new method has the same coding structure and computing complexity

and it can accurately control the compression image quality with an average control precision less than 1%. In addition

this proposed method has higher global compression im-age peak signal to noise ratio at the same total coding rate for sequence remote sensing images.

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Keywords

references

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