
A closed‑loop color feedback algorithm that leverages post‑ISP statistics to improve camera color quality is presented. Unlike traditional approaches, which evaluate white balance and color early in the pipeline and tune individual modules in isolation, the proposed method assesses color near the end of the ISP pipeline, compares it against target perceptual colors, and feeds the resulting deviations back to upstream processing blocks. This enables dynamic adjustment of AWB and color‑related parameters to achieve desired perceptual color outcomes. The framework addresses key limitations of conventional color processing, including (1) evaluating AWB in the raw domain where perceived color cannot be reliably assessed, (2) the inability of fixed color‑tuning parameters to compensate for deviations introduced by other ISP blocks, and (3) the lack of coordinated color evaluation across modules. We further demonstrate an application of this framework for skin‑tone improvement. The system takes face regions, filters non‑skin pixels, computes representative skin color statistics, compares them with target skin colors, and derives adjustment parameters that update color tunings for the current or subsequent frame. This example illustrates the flexibility and effectiveness of the proposed closed‑loop approach for perceptually guided color enhancement or accurate color reproduction.

Skin tone reproduction has long been a challenge in image processing due to illumination by multiple sources in real‐world conditions. This paper describes an algorithm to achieve preferred skin tone reproduction. The work comprises two pivotal components including to develop: 1) a CCT-SPQ/D optimization model via controlled experiments to reveal the mapping relationships between correlated color temperature (CCT) and skin preference quality (SPQ) and chromatic adaptation degree (D), and 2) a novel white balance correction algorithm for skin regions under mixed illumination, which integrates local processing and spatial filtering with color temperature adaptive enhancement via the aforementioned model. Finally, a preference assessment experiment was conducted to demonstrate the superiority of the algorithm proposed.

We have developed a system to measure both the optical properties of facial skin and the three-dimensional shape of the face. To measure the three-dimensional facial shape, our system uses a light-field camera to provide a focused image and a depth image simultaneously. The light source uses a projector that produces a high-frequency binary illumination pattern to separate the subsurface scattering and surface reflections from the facial skin. Using a dichromatic reflection model, the surface reflection image of the skin can be separated further into a specular reflection component and a diffuse reflection component. Verification using physically controlled objects showed that the separation of the optical properties by the system correlated with the subsurface scattering, specular reflection, or diffuse reflection characteristics of each object. The method presented here opens new possibilities in cosmetology and skin pharmacology for measurement of the skin's gloss and absorption kinetics and the pharmacodynamics of various external agents.