Long-exposure shots and flash photography are normally used to acquire images under low-light conditions. However, flash photography often induces color distortion and creates a red-eye effect, while long-exposure shots are prone to motion blur due to camera shake or subject motion. Thus, multi-spectral flash imaging has recently been introduced to overcome the limitations of traditional low-light photography. Multi-spectral flash imaging combines invisible and visible spectrum images, but most multi-spectral flash approaches result in color distortion due to the lower accuracy of the invisible spectrum image. Accordingly, this article presents a multi-spectral flash imaging algorithm using optimization with a weight map to improve the color accuracy and brightness of the image. First, UV/IR and visible spectrum images are captured. To compensate the luminance values under low-light conditions, adaptive tone reproduction is performed using the Naka–Rushton equation. Next, to discriminate uniform regions from detail regions, a weight map is generated using a Canny operator. Finally, the optimization process takes account of the likelihood of the visible light image, the sparsity of the image gradients, and the spectral constraints of the IR and UV channels. The performance of the proposed method is subjectively evaluated using a z-score, and the resulting images are confirmed to have an improved color accuracy and lower noise when compared with the results of other methods.