Performance evaluation of image fusion techniques for Indian remote sensing satellite data using Z-test

다국어 초록 (Multilingual Abstract)

Image fusion is being used since last two to three decades in remote sensing for improving visual appearance of coarse resolution imagery using fine spatial resolution data. The resultant outputs are being used successfully in various applications such as image classification, feature extraction, digital change detection, and many more including multi-temporal and multi-scale change detection.
Acceptability of a fusion method for a particular application depends upon various factors; one of them is quality of fused image. In this research paper the four different image fusion techniques namely Ehlers, IHS fusion, Brovey and FuzeGo have been evaluated using IRS-P6 (Cartosat-1) and RESOURCESAT-2 (LISS-IV) images of Bhopal city, India. Quality of fusion results is assessed by performing visual analysis between fused image and multispectral (MS) image along with statistical analysis. Visual comparison is done based on better visibility of different land cover features such as roads, buildings, water body and sharpness of edges present in image. For statistical evaluation of fusion process, six statistical parameters i.e. standard deviation (SD), correlation coefficient (CC), entropy/ noise, RMSE and ERGAS have been used. In addition to these traditional statistical measures, Z-test is used for combined assessment of fusion techniques. Visual comparisons of fusion results obtained for test site have shown that FuzeGo algorithm has given comparatively better results than other algorithms. Statistical parameter CC, SD are found highest for IHS method, RMSE, and ERGAS are found highest for Brovey method and least noise is added by FuzeGo algorithm. Overall visual analysis and Z-test indicates that FuzeGo has given better results which are followed by Ehlers as compare to other methods.

참고문헌 (Reference)

1 Zhang, Y., "System and method for image fusion"

2 Ehlers, M., "Spectral characteristics preserving image fusion based on Fourier domain filtering" 5574 : 1-13, 2004

3 Alparone, L., "Remote sensing image fusion., Signal and image processing of earth observations series" CRC Press Taylor & Francis Group 2015

4 Vijay Solanky, "Pixel-level image fusion techniques in remote sensing: a review" 대한공간정보학회 24 (24): 475-483, 2016

5 Pohl, C., "Multisensor image fusion in remote sensing : Concepts, methods and applications" 19 (19): 823-854, 1998

6 Pohl, C., "Multisensor image fusion guidelines in remote sensing" 2016

7 Manfred Ehlers, "Multi-sensor image fusion for pansharpening in remote sensing" Informa UK Limited 1 (1): 25-45, 2010

8 Hallada, W. A., "Image sharpening for mixed spatial and spectral resolution satellite systems" Environmental Research Institute Michigan 1023-1032, 1983

9 Damera-Venkata, N., "Image quality assessment based on a degradation model" 9 (9): 636-650, 2000

10 Wald, L., "Fusion of satellite images of different spatial resolutions : Assessing the quality of resulting images" 63 (63): 691-699, 1997

11 Wald, L., "Data fusion–Definitions and architectures—Fusion of images of different spatial resolutions" E ´ cole de Mines de Paris 2002

12 Aiazzi, B., "Context-driven fusion of high spatial and spectral resolution images based on oversampled multi-resolution analysis" 40 (40): 2300-2312, 2002

13 Alparone, L., "Comparison of pansharpening algorithms : Outcome of the 2006 GRS-S Data-Fusion contest" 10 : 3012-3021, 2007

14 Zhang, Y., "A review and comparison of commercially available pan- sharpening techniques for high resolution satellite image fusion" 182-185, 2012

15 Alparone, L., "A new method for MS ? pan image fusion assessment without reference" 3802-3805, 2006

16 Zhang, Y., "A new merging method and its spectral and spatial effects" 20 (20): 2003-2014, 1999

17 Alparone, L., "A global quality measurement of pan-sharpened multispectral imagery" 1 (1): 313-317, 2004

18 Karathanassi, V., "A comparison study on fusion methods using evaluation indicators" 28 (28): 2309-2341, 2007

19 Sasikala, M., "A comparative analysis of feature based image fusion methods" 6 (6): 1224-1230, 2007