Adaptive Dynamic Range Compression Method for Panchromatic Images Based on Detail Regions Gradient Preservation

ABSTRACT An effective panchromatic remote sensing image dynamic range compression method is proposed to solve the issue in existing panchromatic remote sensing image grayscale conversion algorithms, which tend to cause overexposure in certain areas or overall excessive darkness. This method employs an empirical approach of detail region extraction and optimal parameter selection based on gradient to achieve dynamic range compression. First, a novel adaptive detail segmentation method based on the expansion of detail points within image blocks is introduced. Second, a detail optimisation module is established based on local detail preservation, which optimises the extraction of detail regions using gradient‐based Otsu segmentation results and improved CLAHE‐gradient‐based Otsu segmentation results. Then, candidate adaptive dynamic range compression coefficients are determined based on the extracted detail layers, and the optimal adaptive dynamic range compression parameters are selected based on the high gradient proportion of the detail regions. Simulation experiments are conducted on multiple panchromatic remote sensing images with different scenes using the proposed method, and the effects of various dynamic range compression methods are evaluated based on multiple metrics. The results indicate that the proposed dynamic range compression method demonstrates excellent performance.