Vector quantization for entropy coding of image subbands is investigated. Rate distortion curves are computed with mean square error as a distortion criterion. The authors show that full-search entropy-constrained vector quantization of image subbands results in the best performance, but is computationally expensive. Lattice quantizers yield a coding efficiency almost indistinguishable from optimum full-search entropy-constrained vector quantization. Orthogonal lattice quantizers were found to perform almost as well as lattice quantizers derived from dense sphere packings. An optimum bit allocation rule based on a Lagrange multiplier formulation is applied to subband coding. Coding results are shown for a still image.

In this paper, a new measurement method of the rotation angle of a rotor, which is named the 'visual encoder,' was proposed. This method is based on the principles of the vision-based method and the optical encoder, and realized by using a high-speed vision system. The visual encoder shows advantageous features such as non-contact, high-resolution and robustness against the free motion and the fluctuation of the rotation axis. A high resolution method to increase the measurement resolution was also suggested. The accuracy and the robustness of the visual encoder were confirmed through the experimental verifications, and the operation was possible at 6,000 rpm even under the fluctuation of rotation axis.