The influence of noise is an important problem on image acquisition and transmission stages. The traditional image denoising approaches only analyzing the pixels of local region with a moving window, which calculated by neighbor pixels to denoise. Recently, this research has been focused on the transform domain and feature space. Compare with the traditional approaches, the global multi-scale analyzing and unchangeable noise distribution is the advantage. Apparently, the estimation based methods can be used in transform domain and get better effect. This paper proposed a new approach to image denoising in orthonormal wavelet domain. In this paper, we adopt Stein's unbiased risk estimate (SURE) based method to denoise the low-frequency bands and the feature patches distance constraint (FPDC) method also be proposed to estimate the noise free bands in Wavelet domain. The key point is that how to divide the lower frequency sub-bands and the higher frequency sub-bands, and do interscale SURE and intrascale FPDC, respectively. We compared our denoising method with some well-known and new denoising algorithms, the experimental results show that the proposed method can give better performance and keep more detail information in most objective and subjective criteria than other methods.

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.

The full liquid crystal display (LCD) simulation with real transistors and other active components is unrealistic. Because a flat panel display (FPD) includes thin-film-transistors (TFT's) whose number is, at least, the number of total pixels. It hits the simulation limit of SPICE if the number of transistors are more than 0.5 million. This paper demonstrates a new, fast, and effective simulation method for a full LCD panel. The method makes it possible to simulate large LCD panels whereas the conventional method cannot handle. The simulation circuit consists of a-Si TFT model presented earlier, the liquid crystal, the pixel macro models, and interconnects. We show the model parameter extraction and the pixel macro modeling process associated with the simulation results. Using the simulation method presented here some larger LCD panels can be accurately simulated in less than a minute on a workstation.