Thermal-fixing holographic storage in photorefractive crystals is an effective nonvolatile storage technique for stabilizing holograms against the optical erasure. The developing characteristics of fixed holograms in iron-doped lithium niobate dominate their final diffraction efficiencies after developing, provided that the ionic compensation in the fixing stage is nearly complete. Developing kinetics of fixed holograms under homogeneous illumination is studied. The effect of developing light intensity on developing efficiency has been demonstrated experimentally. The fixed holograms with the same initial recording grating strength are developed under illumination of the different light intensities, such as 200mW/cm<sup>2</sup>, 400mW/cm<sup>2</sup>, 600mW/cm<sup>2</sup>, and 800mW/cm<sup>2</sup>, respectively. The fixed holograms with the different initial recording grating strengths are developed under illumination of the same light intensities as well. The overdeveloping characteristics of fixed holograms are described. The developing efficiency of the hologram with a given initial recording grating strength is found to depend on the intensity of developing light. These features can be explained with the joint effect of the resulting space-charge holographic field of the fixed hologram and the photovoltaic field under homogeneous illumination.
The paper provides a novel algorithm for face rendering applications. Ensuring algorithms of low complexity to render virtual humans in VLBR networks is at the heart of our new facial rendering system. The system differs from others such as parametric animation models and interpolation solutions. The novelties include a dual segment growing algorithm and a heat diffusion rendering method. The extracting process takes into account information both in gradient domain and topographic feature. And segments are used to carry this information, which greatly reduces the transmitted packet size. Face rendering is based on this segment and is carried out like a heat diffusive process. Experimental results, as reported in following, prove that this proposed system. Furthermore this scheme can be extended to deal with more general video or image analysis and synthesis systems.
When enjoying videophone or distant learning, people want to see human face as real as possible even in very low bit rate. How to synthesis human face to deliver over network such as Internet and PSTN draws much attention. Conventional techniques based on low-level features cannot perform the desired operation. While model based method need much prior knowledge. The authors present a new algorithm for human face synthesis. It can give a virtual face based on human vision system for bit rate ranging from several kb/s to tens of KB/s. An Adaptive Face Image Filter(AFIF) is used to attenuate noise and preserve face edges as well as details. A facial region detection method detects those pixels that belong to a face. After that, with a novel facial texture interpolating method, the face is rendered in gray scale. Its key feature is a group of diffuse functions for interpolation. Then color is rendered to the whole face scalable.