异源遥感影像融合的辐射分辨率规范化方法

doi:10.3724/SP.J.1047.2015.00713

摘要/Abstract

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

高永刚, 徐涵秋. 异源遥感影像融合的辐射分辨率规范化方法[J]. 地球信息科学学报, 2015, 17(6): 713-723.DOI:10.3724/SP.J.1047.2015.00713

GAO Yonggang,XU Hanqiu. Standardization of Radiation Resolution for Fusion of Multi-sensor Remote Sensing Images[J]. Journal of Geo-information Science, 2015, 17(6): 713-723.DOI:10.3724/SP.J.1047.2015.00713

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卫星类型	传感器	波段使用情况	空间分辨率（m）	辐射分辨率（bit）	获取时间
Landsat-7	ETM+	多光谱	30	8	2003-05-29
EO-1	ALI	全色	10	16	2003-03-26
IKONOS	AVNIR-2	多光谱	4	11	2003-06-22
		全色	1	11	2003-06-22

融合算法	评价指标
融合算法	D	D_r	RMSE	GVI	ERGAS	CC
Brovey	77.022	1333.736	478.069	248.805	28.673	0.987
BT	117.106	2028.315	724.800	377.297	32.603	0.987
IHS	401.873	7064.376	1224.275	1288.285	31.780	1.000
IHS_TU	534.256	9390.553	2169.392	1712.113	32.510	1.000
PCA	178.130	3130.792	1973.866	570.795	32.113	1.000
SFIM	0.519	8.999	4.540	2.315	1.729	0.893
SVR	1.264	21.489	10.829	5.698	4.137	0.972
Wavelet	20.392	357.142	100.444	80.251	34.973	0.743
Gram-Schmidt	0.604	10.343	6.906	2.843	2.796	0.950
Pansharp	0.957	16.126	7.821	4.490	3.206	0.969
Ehlers	2.267	25.347	6.929	9.080	2.896	0.954

评价指标	量化区间
评价指标	区间（1）	区间（2）	区间（3）	区间（4）	区间（5）	区间（6）	区间（7）
D	0.604	0.823	0.842	0.848	0.847	0.790	0.606
D_r	10.343	13.548	13.891	13.996	13.960	13.544	10.384
RMSE	6.906	8.200	8.382	7.970	7.975	7.874	6.900
GVI	2.843	3.699	3.761	3.739	3.751	3.544	2.832
ERGAS	2.780	3.208	3.278	3.129	3.132	3.080	2.793
CC	0.949	0.526	0.478	0.975	0.972	0.975	0.959

评价指标	量化区间
评价指标	区间（1）	区间（2）	区间（3）	区间（4）	区间（5）	区间（6）	区间（7）	区间（8）
D	0.0033	0.0033	0.0033	0.0033	0.0033	0.0033	0.0033	0.0192
D_r	19.2190	19.2190	19.1905	19.1308	19.1310	19.1308	19.1312	25.3279
RMSE	0.0152	0.0152	0.0152	0.0152	0.0152	0.0152	0.0152	0.0286
GVI	0.0157	0.0157	0.0157	0.0157	0.0157	0.0157	0.0157	0.0198
ERGAS	3.8873	3.8873	3.8951	3.8855	3.8855	3.8855	3.8855	4.3886
CC	0.9795	0.9795	0.9674	0.9789	0.9789	0.9789	0.9789	0.9262

评价指标	量化区间
评价指标	区间（1）	区间（2）	区间（3）	区间（4）	区间（5）
D	0.0052	0.0052	0.0052	0.0052	0.0179
D_r	32.7489	32.7497	32.7497	32.9489	39.6572
RMSE	0.0227	0.0227	0.0227	0.0227	0.0275
GVI	0.0023	0.0023	0.0023	0.0023	0.0039
ERGAS	3.9744	3.9743	3.9744	3.9744	4.1326
CC	0.9521	0.9521	0.9521	0.9521	0.8736