AN OPTIMUM THEOS PAN-SHARPENING METHOD EVALUATION USING MULTI-CRITERIA DECISION ANALYSIS
Keywords:
Pan-sharpening methods, THEOS data, image quality criteria, multi-criteria decision analysis (MCDA)Abstract
In remote sensing applications, both high spatial and spectral resolutions are frequently required to achieve more spatial details and accurate thematic information extraction.Presently, there is little scientific research for selecting and applying an appropriate pansharpeningmethod to THEOS imagery. The main objective of the study is, therefore, to evaluate the optimum pan-sharpening method for agriculture, forestry, and urban applications based on self-evaluation and the users’ requirements on a multi-criteria decision analysis (MCDA) basis. Herein, 9 selected pan-sharpening methods including theBrovey transform (BT), multiplicative transform (MT), principle component analysis(PCA), intensity hue saturation transform (IHST), modified intensity hue saturation transform (MIHST), wavelet transform (WT), high pass filtering (HPF), Ehlers fusion(EF), and Gram-Schmidt pan-sharpening (GS) are firstly processed and examined by image quality criteria consisting of visual image analysis, edge detection analysis, image quality indices, and the effect on classification accuracy. Then, the optimum pansharpeningmethod is evaluated based on self-evaluation and the users’ requirements withthe simple additive weighting (SAW) method of MCDA.From the results, the most appropriate methods for THEOS pan-sharpening basedon the single image quality criterion by visual image analysis, edge detection analysis,quality indices, and effect on classification accuracy are GS, HPF, MIHST, and EF,respectively. Meanwhile, the optimum THEOS pan-sharpening methods for the agriculture, forestry, and urban applications based on self-evaluation using the SAWmethod with equal weight are HPF, HPF or GS, and GS, respectively. At the same time,GS is the optimum THOES pan-sharpening method in agriculture, forestry, and urbanstudies based on the users’ requirements with specific weight from each in the experts’group. Consequently, the common optimum THEOS pan-sharpening method based onboth approaches was GS, and HPF can be chosen as the optimum pan-sharpening methodwhen software availability is considered. In addition, WT is the most inappropriate THEOS pan-sharpening method in 3 applications. In conclusion, the integration of 4 image quality criteria using the SAW method ofMCDA can be effectively used as a new tool to evaluate the optimum pan-sharpening method via self-evaluation or the users’ requirements in remote sensing applications.
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