A 3 dimensional (3D) error diffusion method based on edge detection for flat panel display (FPD) is presented. The new method diffuses errors to the neighbor pixels in current frame and the neighbor pixel in the next frame. And the weights of error filters are dynamically adjusted based on the results of edge detection in each pixel's processing, which makes the weights coincide with the local edge feathers of input image. The proposed method can reduce worm artifacts and improve reproduction precision of image details.

This paper addresses the problem to extract moving object from the moving background in the mixed domain (MixeD), which makes it possible to carry the filtering in one dimension. Since the velocities of moving object and background are necessary for moving object extraction, we first estimate the velocities based on the appropriate spatial frequency point selection method in the MixeD. Then an optimal filter used for 1-D signal filtering is designed. By filtering 1-D signals over all spatial frequencies, signals with certain velocity vector are extracted, while the extracted image is obtained by applying the 2-D IDFT to the filtered signals. The simulation results show that the method can extract moving object based both on the correctly estimated velocity and the proposed optimal 1-D filter.

The properties of the surface-conduction electron-emitter display (SED) are mainly decided by the surface-conduction electron emitters (SCE), which are normally made from the expensive metal Pd. In this study, we propose to use metal Zn instead of Pd as the emitter material. Both the device electrode and ZnO thin film are deposited by a sputter, and the electron emitters (SCE) are formed by the electro-forming process. The electron emission characteristic is obtained and the luminescence is observed.

A robust moving object velocity estimation method in the mixed domain (MixeD) is proposed. By obtaining phase, that is, normalizing the 1-D complex sinusoid signals with their magnitudes, the velocity estimations of moving objects with conditions such as object rotation, shape and graylevel variation have been accomplished. Based on the appropriate spatial frequency selection, which choose the points where the signals are less influenced by the background and noise, the spectra of these 1-D temporal complex signals in selected points are estimated by FFT. The simulation results show that velocity vectors have been correctly estimated.

To estimate moving object velocity in an image sequence is useful for a variety of applications, such as velocity measurement, computer vision and monitoring systems. An effective way is to approach it in the transform/spatiotemporal mixed domain (MixeD), which transforms the 3-D signal processing problem into 1-D complex signal processing. But it remains a problem how to select several spatial frequency points in the MixeD which may influence the accuracy of velocity estimation and object detection. In this paper, a spatial frequency selection method has been proposed, which can choose the appropriate spatial frequency points out of a number of points in MixeD automatically. So the velocity estimation problem can be addressed by solving the coupled equations established over two selected appropriate points in 2-D spatial frequency domain other than searching for the spectral energy plane over a number of points selected by experience. In this method, evaluation functions corresponding to image sequence with one moving object and two moving objects are established firstly, and the selection is then achieved by using the established evaluation functions together with a threshold. The simulation results show that the proposed method is effective on the appropriate spatial frequency selection.