Colour balance and contrast stretching for sand‐dust image enhancement. Issue 14 (22nd July 2022)

• Record Type: Journal Article
• Authors: Hua, Zhongwei; Qi, Lizhe; Guan, Min; Su, Hao; Sun, Yunquan
• Is Part Of: IET image processing. Volume 16:Issue 14(2022)
• Page Start: 3768
• Page End: 3780
• Publication Date: 2022-07-22
• Subjects: Image processing -- Periodicals; 621.36705
• DOI: 10.1049/ipr2.12592
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract: The increasingly frequent sand‐dust weather in the inland areas seriously affects outdoor vision applications, especially autonomous vehicles and security monitoring. To moderate the image's colour cast and poor contrast caused by sand‐dust weather, an effective approach is proposed in this study to enhance the sand‐dust images. First, the original degraded image's colour cast is corrected by a new colour balance and compensation formula, which compensates the blue and green channel information through numerous yellow channel information caused by sand‐dust scattering before white balance. Next, in order to avoid the new colour deviation, the corrected image is converted from the RGB colour space to the HSV colour space and use the CLAHE to enhance the V component to improve the contrast. Then, a nonlinear gain function is defined to further adaptively sharpen the V component to enhance image details. Finally, the S component is stretched to improve image saturation. The extensive qualitative and quantitative evaluation shows that this method can improve the image edge clarity and contrast, restore good colour fidelity for all sand‐dust images tested. The verification also proves that this method is of much significance in improving the feature point extraction and the target detection results in the sand‐dust weather.