Facial image synthesis creates blurred facial images almost without high-frequency components, resulting in flat edges. Moreover, the synthesis process results in inconsistent facial images, such as the conditions where the white part of the eye is tinged with the color of the iris and the nasal cavity is tinged with the skin color. Therefore, we propose a method that can deblur an inconsistent synthesized facial image, including strong blurs created by common image morphing methods, and synthesize photographic quality facial images as clear as an image captured by a camera. Our system uses two original algorithms: patch color transfer and patch-optimized visio-lization. Patch color transfer can normalize facial luminance values with high precision, and patch-optimized visio-lization can synthesize a deblurred, photographic quality facial image. The advantages of our method are that it enables the reconstruction of the high-frequency components (concavo-convex) of human skin and removes strong blurs by employing only the input images used for original image morphing.