The features of personal skin conditions are often perceived by how they appear on local skin areas. The appearance of a local skin surface depends on two features: the color texture caused by pigment distributions in skin layers and the brightness textures of sulcus cutis and shading. The image analysis of skin conditions requires the decomposition of local skin images into these components. This article proposes a novel method to estimate these local skin properties by referring to the multispectral images of a skin surface. Spectral images are decomposed into color and brightness textures through a multi-resolution analysis with wavelet functions. The pigment distributions are then estimated based on the Kubelka–Munk theory. Photorealistic images of skin with different local skin conditions can be generated by following the reverse process of decomposition based on the adjusted local texture components. The experimental results demonstrated the good feasibility of the proposed method.