基于自适应S曲线变换的红外图像增强

Infrared Image Enhancement Based on Adaptive S-Curve Transformation

随着红外热成像技术的不断发展,红外图像在民用领域和军用领域都得到了越来越广泛的应用。原始红外图像反映的是特定场景的红外辐射分布,其整体视觉效果往往较差,具有对比度不佳和图像纹理细节不清晰的缺点。它在直方图中呈现出灰度值范围较窄和峰值明显的特点,其图像清晰度往往不佳,因而其必须经过图像增强处理才能适于人眼观察。本文提出了一种基于自适应S曲线灰度变换的红外图像增强算法。通过客观评价指标的计算,结合主观评价方法对图像进行对比评价,结果表明本文提出的算法能够提高红外图像的对比度和增强图像细节,在保证图像不失真的基础上有效地改善红外图像的视觉效果。

With the continuous development of infrared thermal imaging technology, infrared image has been increasingly applied in both the civilian and military fields. The original infrared image reflects the infrared radiation distribution of a specific scene, and its overall visual effect is often poor, with poor contrast and unclear texture detail in the image. Therefore, it exhibits a narrow range of grayscale values and obvious peaks in the histogram, and its image clarity is often poor. Therefore, it must undergo image enhancement processing to be suitable for human observation. This article proposes an infrared image enhancement algorithm based on adaptive S-curve grayscale transformation. By calculating the objective evaluation indicator and combining subjective evaluation methods to compare and evaluate images, the results show that the algorithm proposed in this paper can improve the contrast of infrared images and enhance image detail, effectively improving the visual effect of images while ensuring they are not distorted.