Real-time highlight removal using intensity ratio.

In this paper, we propose an efficient method to separate the diffuse and specular reflection components from a single image. The method is built on the observation that, for diffuse pixels, the intensity ratios between the maximum values and range values (maximums minus minimums) are independent of surface geometry. The specular fractions of the image pixels can then be computed by using the intensity ratio. For textured surfaces, image pixels are classified into clusters by constructing a pseudo-chromaticity space, and the intensity ratio of each cluster is robustly estimated. Unlike existing techniques, the proposed method works in a pixel-wise manner, without specular pixel identification and any local interaction. Experimental results show that the proposed method runs 4× faster than the state of the art and produces improved accuracy in specular highlight removal.

Autofocus for multispectral camera using focus symmetry.

A multispectral camera acquires spectral color images with high fidelity by splitting the light spectrum into more than three bands. Because of the shift of focal length with wavelength, the focus of each channel should be mechanically adjusted in order to obtain sharp images. Because progressive adjustment is quite time consuming, the clear focus must be determined by using a limited number of images. This paper exploits the symmetry of focus measure distribution and proposes a simple yet efficient autofocus method. The focus measures are computed using first-order image derivatives, and the focus curve is obtained by spline interpolation. The optimal focus position, which maximizes the symmetry of the focus measure distribution, is then computed according to distance metrics. The effectiveness of the proposed method is validated in the multispectral camera system, and it is also applicable to relevant imaging systems.