New technique for dynamic-range compression and contrast enhancement in infrared imaging systems
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摘要: 动态范围压缩和对比度增强是红外成像的两个关键步骤,如何提升图像细节、抑制失真是红外成像的重要研究课题。提出了一种新的红外图像可视化方法。算法首先通过最小化损失函数的方法将动态范围压缩问题转化为一个二次优化问题;然后通过设定一个指数因子来增强细节,最终能够在提升细节的同时避免产生光晕。使用不同场景采集的多组红外图像进行实验,结果表明所提算法不仅对红外图像的固有特征有很好的抗性,而且处理结果较好。对比其他算法,该方法能够有效提高图像整体对比度,防止平坦区域过度增强,并且抑制了噪声。Abstract: Dynamic range compression and detail enhancement are two important issues for effectively displaying high dynamic range infrared (IR) images on standard dynamic range monitors. Sophisticated techniques are required in order to improve the visibility of the details without introducing distortions. A novel method was introduced for visualization of IR images. The proposed method was composed of two cascaded steps. In the first step, dynamic range compression of infrared images was posed as an quadratic optimization problem that minimize a cost function. In the second step, the detail was enhanced by an specifically designed exponential factor that provided excellent detail visibility and avoid halo artifacts. The performance of the proposed technique was evaluated using a data set of IR images collected from different operating conditions. The results show that the proposed method is insensitive to features occurring in IR image and yield the most visually pleasing outputs. Compared with other algorithms, it can effectively improve the overall contrast, prevent over-enhancement of flat regions and reduce noise visibility.
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Key words:
- dynamic range compression /
- detail enhancement /
- infrared images /
- high dynamic range
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