12位图像数据的压扩变换显示

范赐恩; 吴敏渊; 张立国; 邓德祥; 曹庆源

doi:10.3788/OPE.20111906.1421

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12位图像数据的压扩变换显示

信息科学 | 更新时间：2020-08-12

- 12位图像数据的压扩变换显示
- Companding transformation display for 12 bit image data
- 光学精密工程 2011年19卷第6期页码：1421-1428
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 武汉大学电子信息学院,湖北武汉,中国,430072
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.61072135)()
- DOI：10.3788/OPE.20111906.1421
  中图分类号： TN27;TP391.4
- 收稿日期：2011-02-16，
  
  修回日期：2011-04-01，
  
  网络出版日期：2011-06-25，
  
  纸质出版日期：2011-06-25
- 稿件说明：
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范赐恩, 吴敏渊, 张立国, 邓德祥, 曹庆源. 12位图像数据的压扩变换显示[J]. 光学精密工程, 2011,19(6): 1421-1428

FAN Ci-en, WU Min-yuan, ZHANG Li-guo, DENG De-xiang, CAO Qing-yuan. Companding transformation display for 12 bit image data[J]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1421-1428
范赐恩, 吴敏渊, 张立国, 邓德祥, 曹庆源. 12位图像数据的压扩变换显示[J]. 光学精密工程, 2011,19(6): 1421-1428 DOI： 10.3788/OPE.20111906.1421.

FAN Ci-en, WU Min-yuan, ZHANG Li-guo, DENG De-xiang, CAO Qing-yuan. Companding transformation display for 12 bit image data[J]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1421-1428 DOI： 10.3788/OPE.20111906.1421.

摘要

利用数字通信的压扩变换原理

提出了12位图像数据到8位数据的16折线等比分区映射方法

来实现在8位显示器上显示12位图像数据的信息。推导出图像信号的线性量化和非线性量化信噪比公式

对3种不同量化方法的信噪比进行了比较。结果显示

在小于35 dB处

8位非线性量化信噪比和12位线性量化信噪比一致;而大于35 dB时

量化信噪比平缓稳定上升。实验表明该方法能有效改善图像的弱信号

在8位显示器上清晰地观察到低亮度图像细节。虽然对图像的高亮度部分进行了压缩

但对图像细节和信噪比影响不大。该方法不仅适用于灰度图像

而且适用于彩色图像

实验效果与理论预期完全一致。

Abstract

Based on the digital communication companding transformation principle

a 16-polygonal line geometric partition method which maps 12-bit image data to 8-bit data was proposed to display 12-bit image information on a 8-bit gray scale monitor. The formulas for calculating the linear and nonlinear quantization Signal to Noise Ratio (SNRs) were derived. By comparing SNRs of three different quantization methods

it was indicated that the SNR of 8-bit nonlinear quantization is consistent with that of 12-bit linear quantization at less than 35 dB and that is in the stable increase at large than 35 dB. Experiments show that this method can effectively improve the weak signal of the image

and the details of a low luminance image can be observed clearly on a 8-bit monitor. Although the high luminance part of the image is compressed

it has little affect on the image details and SNRs. The proposed method is applicable to gray images and color images. Experimental results are fully consistent with theoretical expectations.

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references

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