This paper proposes a gonio-spectral imaging system for measuring light reflection on an object surface by using two robot arms, a multi-band lighting system, and a monochrome digital camera. It allows four degrees of freedom in incident and viewing angles necessary for full parametrization of a reflection model function. Spectral images captured for various incident and viewing angles are warped as if they were all captured from the same viewing direction. The intensity of reflected light is thus recorded in a normalized image form for any incident and viewing directions. The normalized images are used to estimate reflection model parameters at each surface point. To ensure point-wise reflection modeling, a calibration method is also proposed based on a geometrical model of the robot arms and camera. The proposed system can deal with objects with surface texture. Experiments are done on system calibration, reflection model, and spectral estimation. The results using colored objects show the feasibility of the proposed imaging system.

The reduction of a structural pattern at specific gray levels or at the special condition of image data has mainly been discussed in digital halftone methods. This problem is more severe in some flat panel displays because their black levels typically are brighter than other displays blocks. The authors proposed an advanced confined error diffusion (ACED) algorithm which was a well-organized halftone algorithm for flat panel devices. In this paper, we extend the ACED algorithm to the multi-level systems, which are capable of displaying more than 2 levels. Our extension has two merits for the hardware implementation. First, it can be processed in real time using the look-up table based method. The second one is the flexibility of selecting the used gray level. This paper discusses the performance of the proposed algorithms with experimental results for natural test images.