A Survey on the Measurement Methods and Applications of Skin Spectral Reflectance

ABSTRACT As the optical fingerprint that reflects the physiological states of skin, the accurate acquisition of skin spectral reflectance is crucial for pathological diagnosis, ensuring digital imaging fidelity, and enabling the quantitative evaluation of cosmetic efficacy. This paper surveys the advancements in skin spectral reflectance measurement techniques and their applications. Regarding measurement methods, spectrophotometry (250–2500 nm) delivers high‐precision single‐point data, while hyperspectral imaging (400–1000 nm) enables spatially resolved spectral analysis for applications like skin cancer detection, albeit with higher costs and lower imaging efficiency. Meanwhile, computational spectral imaging leverages RGB reconstruction to achieve high spatial resolution, though metamerism and generalizability limitations remain unresolved. In the field of skin reflectance applications, current efforts focus on three domains of medical diagnostics (e.g., dermatitis grading and blood oxygen monitoring), digital imaging (e.g., skin tone correction), and cosmetic technology (e.g., dark circle assessment, efficacy testing of cosmetics, and beauty device development). Despite these innovations, limitations such as measurement errors on uneven skin, high equipment costs, hardware constraints, and operational inconsistencies in skin tone calibration continue to pose significant barriers. To overcome these limitations, we proposed leveraging compressed sensing for efficient hardware‐level data acquisition and physics‐constrained meta‐learning algorithms to enhance generalizability. This survey offers insights for advancing skin spectral measurement technologies and their analytical applications.