# Sharpening of Worldview-3 Satellite Images by Generating Optimal High-Spatial-Resolution Images
###### Abstract
Because the DWT and ATWT techniques maintain the size of the decomposed image, they can create a sharpened image with higher spatial quality than the traditional wavelet-based techniques. Pansharpening techniques have recently been developed that employ image pyramids to process panchromatic images whose spatial resolution has been degraded. In particular, techniques that utilize the Laplacian pyramid have been proposed [11; 12]. However, in these techniques, spatial distortions such as blurring or aliasing occur to a greater degree than when using CS-based fusion techniques. To reduce spatial distortion, [PERSON] et al. [13] and [PERSON] et al. [4] proposed an ATWT context-based decision (CBD) technique and a generalized Laplacian pyramid and context-based decision (GLP-CBD) technique. The high-spatial-resolution multispectral images produced through pansharpening techniques distort the spatial and spectral information of the original image. This distortion occurs because the bands of the panchromatic images and those of the multispectral images have different spectral characteristics; the resulting sharpened images with distorted spectral information are difficult to utilize in analyses that rely on spectral characteristics, such as land cover mapping [14]. Recently, images with more than three spatial resolutions or images of spectral wavelengths outside the visible and near-infrared (VNIR) spectral range can be acquired in contrast to only high-spatial-resolution satellite images consisting of panchromatic and multispectral images. Compared to using only images in the visible and near-infrared (VNIR) wavelength range, remotely sensed satellite imagery from the spectral wavelengths of VNIR and shortwave infrared (SWIR) is more effective for analyzing various types of information for tasks such as land cover mapping, cloud detection, environmental monitoring, and change detection. Generally, pansharpening techniques assume that panchromatic images include the spectral wavelength range of multispectral images. However, some panchromatic images of satellite sensors may not include the spectral wavelength range of multispectral images, such as Worldview-2 and WorldView-3. And some satellite sensors may not obtain panchromatic images with high spatial resolution, such as Sentinel-2A. To sharpen images that do not provide panchromatic images, images with a band that contains the highest spatial resolution should be utilized along with panchromatic images, or the optimal combination should be selected to produce an image that contains the best spectral characteristics of the image to be sharpened when many images are available that all have equally high spatial resolution. The above pansharpening techniques were developed for use with typical high-spatial-resolution satellite images that provide panchromatic images; however, they cannot be used with satellite images that are not panchromatic images. To improve the spatial resolution of satellite images that do not provide panchromatic images, the ability to produce optimal panchromatic images is essential; several related studies have been undertaken in recent years. To improve the spatial resolution of hyperspectral images that contained no panchromatic images, [PERSON] et al. [15] proposed both a selected band scheme and a synthesized band scheme to produce optimal panchromatic images. The selected band scheme used correlation analysis, while the synthesized band scheme relied on multiple regression analysis. [PERSON] and [PERSON] [16] proposed a pansharpening technique that replaced the calculated mean results of images with a 10 m spatial resolution with optimal panchromatic images to improve the spatial resolution of Sentinel-2A satellite images and compared the images resulting from various pansharpening techniques. [PERSON] et al. [17] sharpened Sentinel-2A satellite images by applying the selected and synthesized band schemes proposed by [PERSON] et al. [15] and conducted a quantitative evaluation of the pansharpening results according to the algorithms used.