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Gas passive infrared imaging technology with high dynamic range (HDR) offers numerous advantages in monitoring harmful gases, including high sensitivity, large detection range, ability to detect multiple hazardous gas types, and strong long-range detection capabilities. However, HDR images cannot be directly displayed on standard devices and need to be compressed to an 8-bit data width for visualization. Improper compression may lead to loss of detail and reduced contrast. Additionally, gas passive infrared imaging often suffers from poor detail, blurred edges, low signal-to-noise ratio, and limited contrast with the background, resulting in overall visual blurring. To address these challenges, this paper proposes an adaptive enhancement and dynamic compression method specifically designed for 14-bit gas infrared images. This method effectively compresses the background information while preserving and enhancing the texture details of weak gas cloud targets. The proposed methodology involves a hierarchical decomposition of the input image into detail and background layers. Subsequently, each layer undergoes separate processing: the detail layer is subjected to enhancement, while the background layer undergoes dynamic range compression. Finally, the enhanced detail layer and compressed background layer are fused to produce an 8-bit image. A comprehensive evaluation is conducted comparing the proposed algorithm with histogram equalization using both subjective visual assessment and objective evaluation metrics. The results demonstrate that the proposed algorithm successfully enhances the clarity of gas cloud targets, improves overall contrast, and effectively suppresses halo artifacts and image noise.
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