| Old film restoration is one of key technology and has drawn tremendous attention in research of computer vision, digital image processing, digital video processing and digital program non-linear editing technology. In this thesis, the digital film repair scheme, the basic theory of video restoration and mathematical models of several typical artifacts are investigated. By fully taking advantages of the existed video process theory technology on related applications, this thesis deeply analyzes the detection and removal method for stabilization, scratch, flicker, image noise and low light level CCD noise, extend the research upon above artifact features in spacial and temporal field, reduce the complexity of restoration algorithms and improve their repairing effect. In this thesis, we provide some novel corresponding detection and restoration algorithms, which not even enhance the quality of restored sequence, but also improve the efficiency of video encoder when compressing the film sequence degraded by these kinds of artifacts. The creativities and contribution are discussed in detail as follows:Firstly, the technological framework and basic theory of digital video real-time stabilization are presented. Here we review two typical traditional algorithms for video anti-shaking, then propose a real-time video stabilization system, which includes all steps for stabilized video generating. Some innovative designs are presented in global motion analysis, local motion block removal, constraint of limited edge for cropping, frame's edge extending, stabilized frame reconstruction, etc. This system has three working modes, can support different sizes for input and output video. It not only gets good effect on smoothing translation and rotation unsteadiness, but also reaches a high speed performance and fits for many applications on low speed environment, such as the embedded platform.Secondly, we describe the visual feature of line scratch, improve the mathematical model and spacial method of line scratch detection, and then, we reinforce the precision of detection results with a novel temporal refining detector according to the especial motion feature of scratch, which is small and different from the global frame motionThirdly, we present the visual feature of intensity flicker, list several degradation models with different precision, and then we describe two previous recovery method: SLAR algorithm and Roosmalen's iterative algorithm, analyzes the advantage and shortcoming of thesis methods. In order to realize a fast and low complexity restoration, we provide an improved SLAR method (ISLAR) to deal with the quickly moving object. On the other hand, for the sake of getting more accurate restored sequence, we design a block-based method based on a multi-frame statistical average algorithm, which is complicated but effective.Finally, a novel bidirectional detail-preserved spatio-temporal de-noise algorithm is proposed, which consists a noise estimator, a motion detector, a bidirectional detail detector, and a three-frame adaptive weighted filter. This method uses two previous restored frames and the current frame to reduce noise. The filter is suitable for Gaussian noise, but if it is employed to filter the impulse noise or mixed noise, an optional impulse noise detector and an optional CWM filter will be activated to work together. Furthermore, this thesis proposed a spatio-temporal multi-frame average filter to deal with low light level CCD noise. The key part of this filter is a strict block-based motion detector. In order to deal with the false judgment comes from the camera shaking, we employee a global motion estimation (GME) and block-based motion compensation. For the low light level CCD video, this algorithm takes a small amount of calculation but lead a high quality recovery. Actually the filter can not only remove most of luminance noise and color noise caused by LLL background, but also improve the encoding frame rate and reduce the data size of compressed bit stream efficiently.
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