目的 沙尘环境中获取的图像存在颜色失真、对比度低等问题，不利于人眼辨识以及进一步的图像处理。为解决沙尘降质图像的这些问题，提出一种新的基于颜色调整和对比度增强的沙尘降质图像的增强算法。方法 沙尘降质图像增强要解决两个问题，即颜色偏移和对比度增强。基于沙尘降质图像的的颜色直方图存在的集中性、顺序性以及偏离性等特性，使用高斯模型分别对各通道颜色进行建模，进而进行颜色调整。针对颜色调整后的图像存在的整体灰暗，对比度低以及噪声等特点，利用改进的基于奇异值分解的增强算法，从而有效地增加图像对比度并抑制噪声。结果 为了验证本文算法的有效性，与带有色彩恢复的多尺度Retinex算法、GUM算法、Tarel算法、融合算法4种方法进行了对比。从增强结果可以看出，本文算法能够有效解决降质图像的颜色偏移和对比度低的问题，并增强图像的整体视觉效果。结论 本文算法充分利用沙尘降质图像三通道颜色直方图分布的特点，能够快速高效地实现颜色校正，并通过图像频域的奇异值信息进一步提升图像的对比度。经过多幅沙尘降质图像清晰化实验验证，表明本文方法能够实现对不同程度沙尘降质图像的增强，具有较强的适用性。

Objective Images captured during sandstorm conditions frequently feature undesirable color-cast effects and reduced contrast, and are therefore not suitable for object identification on the scene and further image processing. To solve problems of dust-degraded images, a new visibility restoration algorithm based on color adjustment and contrast enhancement is proposed. Method Restoration of dust-degraded images faces two main problems:color cast and contrast enhancement. Through analysis of the color histograms of a large number of dust-degraded images, we summarized three characteristics:aggregation, order, and deviation. Then, we adopted the normal distribution model to describe each color channel. Regarding the difference between the degraded and clear images, we calculated the extension coefficient based on green channel histogram and adjusted the image value ranges through the extension coefficient. After these steps, the color-cast problem was preliminarily eliminated, but the contrast was still relatively low. To further deal with overall dimness, low contrast, and noise, an improved enhancement algorithm based on singular value decomposition was used to obtain the final result. Result To verify the effectiveness of the proposed algorithm, the other four methods were compared. The proposed method could effectively solve the color cast, improve the dust image contrast, and enhance the overall visual effect of the image. Conclusion By taking advantage of the characteristics of three-channel color histogram distribution of dust-degraded images, the proposed method can achieve fast and efficient color correction. Furthermore, the singular value information image in the frequency domain is adopted to enhance contrast. As verified by many dust-degraded image visibility restoration experiments, the method can enhance different dust-degraded levels; thus, it has strong applicability.