The band design of satellite payload is bound up with its application. Generally speaking, visible and near-infrared (NIR) wavelength bands are included. Panchromatic and four multispectral bands, i.e., blue, green, red, and NIR wavelength bands have become the standard configuration of satellite optical payloads. In this study, based on the band settings, in-orbit operation status, imaging conditions and surface features, a color-enhanced remote sensing image processing method for is proposed for earth observation satellites in view of the application requirements. What’s more, the reasonable loading of the NIR band information lays a foundation for subsequent image visual interpretation and application display. Based on the above color restoration and enhancement processing, the brightness and sharpness of the image are enhanced to meet the visual effect by scientifically setting parameters, especially by improving the greenness of vegetation.
The Gaofen-4 satellite (GF-4) is the first Chinese remote sensing satellite to be placed in a geosynchronous orbit, which has a wide range of application prospects. The image sharpness evaluation method is a key step to quickly, accurately and automatically obtain the quality of a large number of GF-4 remote sensing data and understand the changes of the in-orbit satellite. Moreover, the assessment of image sharpness changes is the verification of the stability of the satellite operation, and can also provide reference for the follow-up satellite planning. Taking the time-series GF-4 panchromatic images of Zhengzhou and Chifeng from May 2016 to July 2020 as the data source, we use the block standard deviation sharpness evaluation method based on spatial domain and the power spectrum sharpness evaluation method based on frequency domain to calculate four kinds image sharpness evaluation values and carry out the correlation analysis from the same day and the same month, considering whether to remove the influence of image brightness. We analyze the influence of image brightness on the sharpness evaluation, and explores the applicability of these two methods for GF-4 image, so as to select the best sharpness evaluation method. The results show that the image power spectrum that has been normalized by the average image brightness is the most suitable image sharpness evaluation method for GF-4 image. This method is used to evaluate the image quality of 208 GF-4 panchromatic images in Zhengzhou and Chifeng. The results show that: since the delivery of GF-4 in orbit test satellite, the image sharpness is stable. At the same time, some suggestions are given for the planning of subsequent geosynchronous orbit satellites. It is necessary to improve the anti-interference ability of the camera to the atmospheric conditions, platform jitter and other external conditions.
The IHS transform fusion is one of the most widely used techniques for image fusion. However, the IHS transform fusion brings spectral distortion. In order to develop new image fusion methods, it is necessary to investigate the spectral features of the original images from different sensors. In this study, high-resolution panchromatic images were reconstructed to improve IHS transform based on GF-2 satellite images. The NSCT transform was used in order to separate details and spectral information. A synthetic index (SI) for assessing fidelity was proposed with consideration of average gradient, entropy, correlation coefficient and spectral distortion. Results show that, in urban areas, the SI of improved IHS method increases from 2.75 to 4.30, and the SI of the hybrid method (improved IHS + NSCT method) increases from 6.68 to 6.93. In addition, the proposed method helps to improve the SI from 1.10 to 3.80 and the NSCT from 6.00 to 7.46 for vegetation covered areas. Thus, the improved IHS transform would maintain spectral fidelity and significantly improve the vegetation spectral information.
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