Estimating spectral reflectance of fabrics from high-resolution multi-band HDR images

Material perception of woven fabrics is produced by the geometric factors based on microscopic structure of the fabric surface and optical factors based on reflection and transmission properties of fibers and yarns. In order to faithfully reproduce the material perception of the fabric, we observe the high-resolution multi-band high dynamic range (HDR) image of the reflection of fabric surface in one pixel (size: 5 ~ 7μm), and estimate the spectral reflectance for each pixel using the partial least squares (PLS) method. In PLS method, the training samples corresponding to the observed image and the spectral reflectance that was measured by the spectrophotometer are required. However, spectral reflectance of fabric is higher than training samples such as color patches. Therefore, the estimation accuracy decreased in the range of high luminance compared with the training samples. In this paper, we propose a method for estimating the spectral reflectance of having high reflectance, such as fabric, and show the effectiveness of the proposed method. In addition, we have confirmed that the specular reflection containing the object color is stronger on the high light area of the fabric.