Abstract
Commonly used image fusion techniques generally produce good results for images obtained from the same sensor, with a standard ratio of spatial resolution (1:4). However, an atypical high ratio of resolution reduces the effectiveness of fusion methods resulting in a decrease in the spectral or spatial quality of the sharpened image. An important issue is the development of a method that allows for maintaining simultaneous high spatial and spectral quality. The authors propose to strengthen the pan-sharpening methods through prior modification of the panchromatic image. Local statistics of the differences between the original panchromatic image and the intensity of the multispectral image are used to detect spatial details. The Euler’s number and the distance of each pixel from the nearest pixel classified as a spatial detail determine the weight of the information collected from each integrated image. The research was carried out for several pan-sharpening methods and for data sets with different levels of spectral matching. The proposed solution allows for a greater improvement in the quality of spectral fusion, while being able to identify the same spatial details for most pan-sharpening methods and is mainly dedicated to Intensity-Hue-Saturation based methods for which the following improvements in spectral quality were achieved: about 30% for the urbanized area and about 15% for the non-urbanized area.
Highlights
Data integration is an important and widely developed concept due to the easy access to a large number of different data [1,2,3,4], mainly including image data obtained from the satellite and aerial ceiling [5,6,7] and from low altitudes [8,9,10]
The experiment included pan-sharpening for each dataset using the original panchromatic image and a panchromatic image modified in accordance with the approach proposed by the authors
During the spatial quality assessment, the entire post-fusion images were compared with the original panchromatic image, having all been previously sharpened with a Laplace filter to expose the spatial information
Summary
Data integration is an important and widely developed concept due to the easy access to a large number of different data [1,2,3,4], mainly including image data obtained from the satellite and aerial ceiling [5,6,7] and from low altitudes [8,9,10]. The concept of pan-sharpening, which refers to the fusion of satellite imagery, is popular in remote sensing Such imagery is characterized by different properties and are usually assessed in terms of spatial and spectral resolutions. The interpretation of imagery is, much more successful if there is access to multispectral imagery, in which data is collected in several narrow channels by detectors sensitive to a specific part of the electromagnetic spectrum. Such images allow for a more efficient recognition of objects, based on their different spectral properties.
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