Efficient coding method for deep space detection Bayer pattern image

Jie LEI; Lu-lu YU; Xiao-hong LUO; Yun-song LI

doi:10.3788/OPE.20192701.0191

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Efficient coding method for deep space detection Bayer pattern image

Information Sciences | 更新时间：2020-08-13

- Efficient coding method for deep space detection Bayer pattern image
- Optics and Precision Engineering Vol. 27, Issue 1, Pages: 191-200(2019)
- 作者机构：
  
  西安电子科技大学综合业务网理论及关键技术国家重点实验室，陕西西安 710071
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20192701.0191
  CLC： V19
- Received：08 May 2018，
  
  Accepted：17 July 2018，
  
  Published：15 January 2019
- 稿件说明：
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Jie LEI, Lu-lu YU, Xiao-hong LUO, et al. Efficient coding method for deep space detection Bayer pattern image[J]. Optics and precision engineering, 2019, 27(1): 191-200.
DOI：

Jie LEI, Lu-lu YU, Xiao-hong LUO, et al. Efficient coding method for deep space detection Bayer pattern image[J]. Optics and precision engineering, 2019, 27(1): 191-200. DOI： 10.3788/OPE.20192701.0191.

摘要

本文提出一种基于JPEG2000标准的Bayer图像高性能RBCR(Remove Bayer Component Relation

RBCR)压缩算法。在RBCR压缩算法中，根据Bayer图像相关性较高的特点，对Bayer图像进行颜色分量分离，得到处理单元子图，对各子图进行1×4整型离散余弦变换，降低Bayer图像中各颜色分量空间域内的相关性；对变换后的各分量DCT系数使用标准JPEG2000算法独立完成小波变换、Tier1编码、MQ编码和率失真斜率计算等，再基于率失真斜率联合截取方法完成各个分量的码流截取，即使用相同的率失真斜率门限值，按照率失真斜率值由高到低的顺序依次完成所有分量编码码块的码流截取，最后各个分量的截取结果再进行独立的码流组织输出。在RBCR算法中通过加入DCT变换降低Bayer图像相关性和对各个分量码流的率失真斜率联合截取，提高恢复图像质量且精确控制了码率。实验结果表明，RBCR算法与各个分量独立压缩方法相比，恢复图像质量得到提升，尤其在4倍的压缩倍数下效果最佳，峰值信噪比平均提高1.814 dB

复杂峰值信噪比平均提高2.414 dB。可以满足深空探测低复杂度和高质量图像的要求。

Abstract

Based on the JPEG2000 compression framework

an RBCR compression algorithm for Bayer remote sensing images with high quality was proposed in this study. In this algorithm

the color components of the Bayer image were separated

and the processing unit subgraphs were obtained. Each subgraph undergoes a 1×4 integer discrete cosine transform

so the correlation of the four color component space domain in Bayer images was reduced. The JPEG2000 algorithm was used to perform the wavelet transform

Tier1 coding

MQ coding

and rate-distortion slope calculation on the transformed DCT coefficients; subsequently

the code stream interception of each component was completed based on the rate-distortion slope joint interception method. In accordance with the rate-distortion slope values arranged in descending order to complete the code stream interception of all component encoding code blocks

the interception result of each component was finally subjected to the independent stream organization output. In the RBCR algorithm

by adding the DCT transform to reduce the Bayer image correlation and intercepting the rate-distortion slope of each component stream

the recovery image quality was improved and the code rate is accurately controlled. The experimental results show that

compared with each component independent compression method

the RBCR algorithm has improved image quality. At 4 times the compression ratio

the peak signal-to-noise ratio increased by an average of 1.814 dB

and the signal-to-noise ratio increased by an average of 2.414 dB

which meets the requirements of low computational complexity and high image quality for deep space detection.

关键词

Keywords

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