Hazy Image Enhancement Using DCP and AHE Algorithms with YIQ Colour Space

Abstract

The use of hazy images is amongst the fastest ways to identify natural resources. Aerial photography has overcome the obstacles faced in land areas, such as rugged areas, swamps and sand dunes. It has important applications in tracking and monitoring studies during wars and peace. However, aerial images often suffer from the lack of contrast due to dust and pollutants. Therefore, this study attempts to improve aerial images by modified dark channel prior (DCP) and adaptive histogram equalisation (AHE) algorithms with YIQ. The images are first improved through DCP and then converted into YIQ colour space that saves the chromatic compounds (IQ). The lighting component comes out after improving the original aerial image via the stretch technique and AHE. Afterwards, all the compounds are merged, and reverse transformation is performed. The proposed method for improving aerial photographs was compared with several other methods. By analyzing the results, the proposed method obtained the best measures of quality, including an entropy value of (7.771), an average gradient value of (14.207) and a naturalness image quality evaluator value of (3.700)