Spatial And Spectral Quality Evaluation Based On Edges Regions Of Satellite Image Fusion
This work addresses a specific gap in quality evaluation for satellite image fusion, but it is incremental as it builds upon existing edge detection techniques.
The study tackled the lack of objective spatial resolution assessment for satellite image fusion by proposing a new method based on edge region analysis, achieving evaluation through Contrast Statistical Analysis and color distortion estimation via Histogram Analysis.
The Quality of image fusion is an essential determinant of the value of processing images fusion for many applications. Spatial and spectral qualities are the two important indexes that used to evaluate the quality of any fused image. However, the jury is still out of fused image's benefits if it compared with its original images. In addition, there is a lack of measures for assessing the objective quality of the spatial resolution for the fusion methods. Therefore, an objective quality of the spatial resolution assessment for fusion images is required. Most important details of the image are in edges regions, but most standards of image estimation do not depend upon specifying the edges in the image and measuring their edges. However, they depend upon the general estimation or estimating the uniform region, so this study deals with new method proposed to estimate the spatial resolution by Contrast Statistical Analysis (CSA) depending upon calculating the contrast of the edge, non edge regions and the rate for the edges regions. Specifying the edges in the image is made by using Soble operator with different threshold values. In addition, estimating the color distortion added by image fusion based on Histogram Analysis of the edge brightness values of all RGB-color bands and Lcomponent.