White Balance Research: Thesis, Implementation Code, and Experimental Images

This research paper and accompanying codebase address the critical importance of white balance in image processing, presenting developed algorithms and experimental outcomes. White balance serves as a fundamental image processing task that enhances color authenticity and accuracy in digital imagery. The study's contributions hold significant relevance for digital photography, computer vision, and image processing domains. Beyond theoretical discussions on white balance methodologies, the package includes practical implementations featuring key functions such as color temperature adjustment algorithms, gray world assumption implementations, and color correction techniques. The provided experimental images demonstrate various lighting conditions and corresponding correction results, offering valuable reference material for understanding real-world applications. These resources present substantial educational and practical value, worthy of download and detailed examination.