利用H.264多幅畫面追蹤之
視訊雜訊消除技術
摘 要
在許多實際的視訊系統中，由於環境亮度不足造成感測器過熱、或感測器元件故障等因素，使得視訊在擷取、傳輸時可能會產生高斯、突波雜訊。這些雜訊會影響系統輸出的視訊品質及壓縮效率，因此雜訊消除是視訊處理中必要的一環。以往的濾波器若只考慮利用空間域上的資訊做雜訊衰減，會有殘影的情況發生；若只考慮利用時間域上訊號間的相關性來濾除雜訊，則無法消除短暫突發性的雜訊。我們提出利用H.264精準的移動補償及多幅參考畫面特性之空間-時間域濾波器。我們利用H.264多種區塊模式決策，一方面決定是否畫面受到雜訊干擾，另一方面也決定適當參數提供空間域濾波使用。在時間域方面，我們參考多張前畫面，根據移動軌跡找出可參考的像素，利用MSE評估時間域上像素間的相似性來排除雜訊。我們所提出的可調式的空間域濾波器及非線性的時間域濾波器，最後實驗數據顯示，可以有效達到消除高斯雜訊後PSNR提升0.83dB以上，位元率可減少24.46%以上；消除突波雜訊後PSNR可提升8.17dB以上，位元率減少84.85%以上，都有不錯的效果。
Video
noise reduction using H.264
multi-frame trajectory
In video capture, noises such as Gaussian
and impulse noise may exist because of insufficient luminance or defect of
image sensors. Noise in video will seriously affect human visual perception and
reduce compression efficiency. Therefore, noise reduction is a necessary part
of video processing. Spatial filter and temporal filter were proposed to reduce
noise in video in previous works. Both of them have disadvantages such as ghost
effect of spatial filtering and blurring in temporal filtering. Consequently, we propose a spatio-temporal
filtering scheme that utilizes motion compensation with multi-reference frames
in H.264 to remove noise. It utilizes the variation of inter mode distributions
to detect noise and determine the parameters for spatial filter. In the time domain, a reference pixel is
selected from multi-reference frames according to the motion trajectory and MSE
criterion. The proposed adaptive spatial filter and non-linear temporal filter
can effectively remove Gaussian and impulse noises to improve video quality up
to 0.83dB and 8.17dB in PSNR respectively. Meanwhile, it can also boost the
compression efficiency by reducing the bitrate up to
84.85% in our experiments.