奇异值非线性修正的低对比度红外图像实时增强

由于场景中目标与背景的温差相对较小,红外图像会存在对比度低、视觉效果差的问题,针对这一问题,提出一种基于奇异值非线性修正的红外图像对比度实时增强方法。该方法首先对红外图像进行奇异值分解得到其原始奇异值,然后采用一个对数型非线性变换对图像奇异值进行优化,最后根据修正的奇异值重构出对比度增强的红外图像。利用对数型非线性变换修正图像奇异值不仅能够有效拉伸奇异值的动态范围,同时可优化奇异值的变化梯度,使图像的能量信息得到更充分地表达,改善红外图像不良的视觉效果。实验结果表明,该方法较几种对比方法在视觉效果和客观评价方面均具有更优的增强性能;同时体现出良好的实时性,为实现红外图像的实时增强提供了新途径。

Low-contrast infrared image real-time enhancement based on singular value nonlinear correction

Due to the small temperature difference between target and background in the scene, infrared image usually has a low contrast and poor visual effect. In order to solve this problem, a novel enhancement method for low-contrast infrared image is proposed based on nonlinear correction of singular values in real time. Firstly, the infrared image is processed by means of singular value decomposition to obtain the original singular values. Then, logarithmically nonlinear transformation is adopted to optimize singular values. Finally, the enhanced infrared image is reconstructed with new singular values corrected. Using logarithmically nonlinear transform can stretch the dynamic range of singular values, and optimize gradient of singular values with the result that the energy information of infrared image can be expressed fully and that the quality of infrared image can be improved effectively. The experimental results show that the proposed method outperforms other methods in terms of visual effect and objective evaluation and also reflects a good real-time performance, which provides a new approach for the realization of real-time infrared image enhancement.