The human eye usually experiences a loss of color sensitivity when it is subjected to high levels of luminance, and perceives a discrepancy in color between high and normal-luminance displays, generally known as a hue shift. Accordingly, this paper models the hue-shift phenomenon and proposes a hue correction method to provide perceptual matching between high and normal-luminance displays. The modeling of the hue-shift phenomenon is determined by perceived hue matching experiments. To quantify the hue-shift phenomenon for the whole hue angle, 24 color patches with the same lightness are first created and equally spaced inside the hue angle for three lightness levels. These patches are then displayed one-by-one on both displays with the ratio of luminance between the two displays. Next, the hue value for each patch appearing on the high luminance display is adjusted by observers until the perceived hue for the patches on both displays appears the same visually. After obtaining the hue-shift values from the perceived hue matching experiment, these values are fit piecewise into seven sinusoidal functions to allow the shifted-hue amounts to be approximately determined for arbitrary hue values of pixels in a high luminance display and then used for correction. Essentially, the input red green blue (RGB) values of an image are converted to CIELAB values by a forward characterization model, and then, LCh (lightness, chroma, and hue) values are calculated to obtain the hue values for all the pixels. These hue values are shifted according to the amount calculated by the functions of the hue-shift model. Finally, the corrected CIELAB values are calculated from lightness, chroma, and corrected hue values, and after that, the output RGB values for all pixels are estimated by an inverse characterization model. For evaluation, an observer's preference test was performed using several test images with other hue shift results and the comparison results are shown with a z score.