A Fast Sand-dust Image Enhancement Algorithm by Blue Channel Compensation and Guided Image Filtering

Abstract

Computer vision systems are significantly impacted by the color variation and low visibility of images taken under sand-dust conditions To address the aforementioned issues, we provide a quick and efficient algorithm to improve photos taken under sand-dust situations. The loss value in the blue channel is first adjusted for. Subsequently, the image deteriorated by sand and dust is color corrected using white balance technology. Lastly, the picture contrast and edge correctness are improved using guided image filtering, and the image detail information is improved by using an adaptive method to determine the detail layer's magnification factor. The approach can successfully restore the fading features of sand-dust-deteriorated photos, according to the experimental results on a sizable number of degraded images by the dust in a brief amount of time, and enhance image sharpness. The suggested method may greatly improve the photos taken during sand-dust weather conditions, as shown by experimental findings via qualitative and quantitative assessments, and the outcomes are superior to those of other ways.