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.