Optimal spectral and spatial weights for photometric stereo for accurate shape reconstruction

A photometric stereo method is optimized in view of signal-to-noise-ratio(SNR) in both the spectral and spatial domain to accurately reconstruct the shapes for wide spectral band objects. Optical polarization filters are used to capture images free from specular reflection components so that the reflection can be approximated to Lambertian. The Jacobi iterative method is applied to solve the equalities between the images and the reflection model for shape. The reconstruction is optimized in view of SNR using the albedos as spatial weights and average albedo values as spectral weights. It is further optimized doubly using the albedos to suppress effects of noise most noticeable in black regions of objects and using a spatial weight dependent on the degree of saturations. Experimental results show that the optimization is very effective to obtain good shapes for wide spectral band objects with minimal effects of reflection models different from the Lambertian.