The colors of objects in natural images are affected by the color of lighting, and accurately estimating an illuminant's color is indispensable in analyzing scenes lit by colored lightings. Recent lighting environments enhance colorfulness due to the spread of light-emitting diode (LED) lightings whose colors are flexibly controlled in a full visible spectrum. However, existing color estimations mainly focus on the single illuminant of normal color ranges. The estimation of multiple illuminants of unusual color settings, such as blue or red of high chroma, has not been studied yet. Therefore, new color estimations should be developed for multiple illuminants of various colors. In this article, we propose a color estimation for LED lightings using Color Line features, which regards the color distribution as a straight line in a local area. This local estimate is suitable for estimating various colors of multiple illuminants. The features are sampled at many small regions in an image and aggregated to estimate a few global colors using supervised learning with a convolutional neural network. We demonstrate the higher accuracy of our method over existing ones for such colorful lighting environments by producing the image dataset lit by multiple LED lightings in a full-color range.