地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (6): 713-723.doi: 10.3724/SP.J.1047.2015.00713

• 遥感科学与应用技术 • 上一篇    下一篇

异源遥感影像融合的辐射分辨率规范化方法

高永刚, 徐涵秋   

  1. 1. 福州大学环境与资源学院,福州 350116
    2. 福州大学遥感信息工程研究所,福州 350116
  • 收稿日期:2014-08-24 修回日期:2014-09-22 出版日期:2015-06-10 发布日期:2015-06-10
  • 作者简介:

    作者简介:高永刚(1976-),男,博士,讲师,主要从事遥感图像处理和卫星测高研究。E-mail: yggao@fzu.edu.cn

  • 基金资助:
    福建省自然科学基金项目(2012J01171、2012J01169);国家科技支撑计划项目(2013BAC08B01-05);海岛(礁)测绘技术国家测绘地理信息局重点实验室基金(2010B09)

Standardization of Radiation Resolution for Fusion of Multi-sensor Remote Sensing Images

GAO Yonggang*(), XU Hanqiu   

  1. 1. College of Environment and Resources, Fuzhou University, Fuzhou 350108, China
    2. Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou 350108, China
  • Received:2014-08-24 Revised:2014-09-22 Online:2015-06-10 Published:2015-06-10
  • Contact: GAO Yonggang E-mail:yggao@fzu.edu.cn
  • About author:

    *The author: SHEN Jingwei, E-mail:jingweigis@163.com

摘要:

遥感影像融合算法,在增强多光谱影像空间分辨率的同时,可实现影像间的信息互补,提高遥感影像的解译能力。异源影像的融合受影像间配准精度及其在时相、空间分辨率和辐射分辨率之间差异的影响,而不同辐射分辨率对异源遥感影像融合所产生的影响及其纠正方法还缺乏深入的研究。为此,本文提出了异源影像融合的辐射分辨率规范化方法。该方法在统一像元值量化区间的基础上,将其乘以相同的比例系数转换到更高的辐射分辨率的量化区间,以减小融合过程由于数据位数取舍而引起的影像信息丢失。研究表明:本文所提出的辐射分辨率规范化方法的取整融合或以实数形式融合,其结果几乎没有差别;而其他转换方法的取整结果均较实型结果差。由于直接采用反射率值进行融合会使其结果产生严重的光谱失真,因此,应采用辐射分辨率规范化方法将反射率值进行转换后再做融合。

关键词: 影像融合, 辐射分辨率规范化, 量化区间, 异源影像, 光谱保真度

Abstract:

Today, an abundant supply of remote senseing data with various spatial, radiative and spectral resolutions from multi-platforms has provided rich sources of information for scientific research. In order to overcome the limitation of a particular type of remote sensing data in application, and take the full advantage of other remote sensing data, image fusion technique has been frequently used to enhance the resolution of remote sensing data and perform scale transformation among images obtained from different remote sensing platforms. A proper image fusion algorithm can not only improve the refinement of details of a low-resolution multispectral image, but also preserve its spectral information. Moreover, it can utilize the complementary information, reduce the data redundancy, and enhance the interpretation ability of the images. The fusion result is influenced by many factors, such as image fusion algorithm, seasonal difference, registration error, spatial and radiation resolution difference, etc. The images used in this study have different radiation resolutions, including 8 bit, 11 bit and 16 bit. In order to reduce the influence of differences in the radiation resolution and in the resultant data dynamic range on image fusion, this paper proposed a method for the standardization of radiation resolution. Based on the unification of quantization intervals for digital number, the transformation from low to high radiation variability through multiplication of a same proportion coefficient can reduce the loss of image information, which is caused by data bits conversion in the fusion process. The results show that the proposed standardization method of radiation resolution can be applied to remote sensing data with different quantization intervals and is easy to be programmed. When using the proposed standardization method for fusing different images, the resultant fusion results are almost identical to each other, either using real number value or integer value. Whereas, when using other quantization methods, the resultant fusion image with real number value is generally better than that with integer value. The standardization of radiation resolution is a necessary step for image fusion when using reflectance-based images, because all image fusion algorithms will cause a serious spectral distortion to the fusion results.

Key words: image fusion, standardization of radiation resolution, quantization interval