As digital still cameras become popular and accordingly their image quality becomes more of a concern, there are increasing studies in reducing the gap between human-observed scenes and images captured by digital still cameras. The dynamic range of a digital camera is narrower in contrast to the one of the scene, thus it is hard to recognize an object in the shadow region of a captured image. The Retinex algorithm is generally used to improve detail and local contrast of the shadow region in an image by dividing the image by its local average image, regarded as a local illuminant, using a Gaussian filter. The result by retinex algorithm depends on the scale of the Gaussian filter. The smaller the Gaussian filter, the more improved the local contrast, but brings the graying-out and halo artifact. Thus, to reduce those artifacts, a multi-scaled retinex algorithm was developed based on the weighted sum of several resulting images from the retinex algorithm by various-scaled Gaussian filters. However, if the chromatic distribution of the original image is not uniform and dominated by a certain chromaticity, the chromaticity of the local average image depends on the dominant chromaticity of the original image, thereby the colors of the resulting image divided by the local average image are shifted to a complement color to the dominant chromaticity of the original image. In this paper, a modified multi-scaled retinex method to reduce the influence of the dominant chromaticity in the image is proposed. For this, first, the local average images are divided by the average chromaticity values of the original image. And then, the local average images are multiplied by the chromaticity of the global illuminant, which is estimated by the averaged chromaticity values within the highlighted region, to consider its influence on the local illuminant. In addition, to compensate for the graying-out effect, the chroma value of the output image is enhanced based on that of the original image in the CIELAB space. Experimental results show that the proposed method improved the local contrast and detail without color distortion, thereby improving the color rendition.