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. 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. 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. 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.