Histogram modification based pansharpening by using differential evolution algorithm

Abstract

SUMMARY Optic geo‐observer satellites acquire multispectral images (MSI) with low spatial resolution and panchromatic images (PAN) with high spatial resolution, due to communication band‐limits and the necessity of using on‐board energy efficiently. Histogram modification is an image processing method that alters the intensity values of an image to improve contrast. The Histogram Modification based Pansharpening (HMP) method has been proposed in this article for injecting high‐resolution spatial information of PAN into MSI with limited color degeneration to generate a pansharpened image (PSI). The differential evolution algorithm (DE) has been used to optimize the internal parameters of the HMP. HMP uses three different blind‐image quality metrics to avoid from artificial spectral and spatial defects generally appeared in PSI. The quality of PSI generated by HMP has been statistically compared to the PSIs produced by 17 different pansharpening methods by using 10 different image quality metrics. In the tests performed, three different test image sets acquired by geo‐observation satellites have been used. Test image sets are covering the areas with different spatial and spectral characteristics. HMP outperforms the other state‐of‐the‐art pansharpening methods used in this article, according to the statistical analysis results. HMP is highly effective at reliably preserving spectral and spatial fidelity.