Image Colour Correction of Smartphone-based Imaging Devices for Medical Application: A Literature Review

Abstract

Smartphone technology has revolutionised the field of digital imaging, especially in healthcare and medical applications. Smartphones equipped with built-in high-resolution imaging capabilities, smartphone-based imaging devices have become cost-effective and powerful tools for health monitoring and diagnosis. However, the colour information of the images captured by different smartphone models varies from one to another, which introduces the colour distortion. These colour distortions may negatively impact image interpretation, diagnosis accuracy, and subsequent deep learning based medical analysis. In this context, the field of colour constancy algorithms has become extremely important in providing accurate and consistent colour representation in digital images. Colour constancy has gained significant scientific interest in the last two decades due to its crucial role in mitigating colour distortions caused by varying image acquisition conditions. These algorithms are essential pre-processing steps to standardise colour representation across different devices and imaging conditions, thus reproducing images that accurately represent real-world scenes. Over the years, many studies have been conducted on the colour constancy topic to improve its effectiveness and accuracy in various domains. This paper reviews significant contributions to colour constancy algorithms over the past 10 years, including the fundamentals of image formation, colour correction algorithms in conventional applications, and colour correction algorithms in the medical field. By offering a comprehensive overview of these key topics, the paper highlights the potential of smartphone-based imaging and colour constancy algorithms in advancing healthcare applications and enhancing diagnostic accuracy.