School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China.
Key Laboratory of Signal Detection and Processing, Xinjiang University, Urumqi 830046, China.
Sensors (Basel). 2022 Mar 1;22(5):1918. doi: 10.3390/s22051918.
The scattering and absorption of light results in the degradation of image in sandstorm scenes, it is vulnerable to issues such as color casting, low contrast and lost details, resulting in poor visual quality. In such circumstances, traditional image restoration methods cannot fully restore images owing to the persistence of color casting problems and the poor estimation of scene transmission maps and atmospheric light. To effectively correct color casting and enhance visibility for such sand dust images, we proposed a sand dust image enhancement algorithm using the red and blue channels, which consists of two modules: the red channel-based correction function (RCC) and blue channel-based dust particle removal (BDPR), the RCC module is used to correct color casting errors, and the BDPR module removes sand dust particles. After the dust image is processed by these two modules, a clear and visible image can be produced. The experimental results were analyzed qualitatively and quantitatively, and the results show that this method can significantly improve the image quality under sandstorm weather and outperform the state-of-the-art restoration algorithms.
光的散射和吸收导致沙尘暴场景中的图像退化，容易出现色彩失真、对比度低和细节丢失等问题，从而导致视觉质量较差。在这种情况下，由于色彩失真问题的持续存在以及场景传输图和大气光的估计不佳，传统的图像恢复方法无法完全恢复图像。为了有效纠正色彩失真并增强沙尘图像的可见度，我们提出了一种使用红、蓝通道的沙尘图像增强算法，该算法由两个模块组成：基于红色通道的校正函数（RCC）和基于蓝色通道的尘粒去除（BDPR）。RCC 模块用于校正色彩失真，BDPR 模块则用于去除沙尘颗粒。经过这两个模块处理后的尘雾图像可以生成清晰可见的图像。我们对实验结果进行了定性和定量分析，结果表明，该方法可以显著提高沙尘暴天气下的图像质量，优于最先进的恢复算法。
