In complementary metal oxide semiconductor image sensor (CIS) industry, advances of techniques have been introduced and it led to unexpected artifacts in the photograph. The color dots, known as false color, also appear in images from CIS employing the modified color filter arrays and the remosaicing image signal processors (ISPs). Therefore, the objective metric for image quality assessments (IQAs) have become important to minimize artifacts for CIS manufacturers. In our study, we suggest a novel no-reference IQA metric to quantify the false color occurring in practical IQA scenarios. We propose a pseudo-reference to overcome the absence of reference image, inferring an ideal sensor output. As we detected the distorted pixels by specifying outlier colors with a statistical method, the pseudo-reference was generated while correcting outlier pixels with the appropriate colors according to an unsupervised clustering model. With the derived pseudo-reference, our method suggests a metric score based on the color difference from an input, as it reflects the results of our subjective false color visibility analysis.