本文選題：塊匹配 + 運(yùn)動估計��； 參考：《山東大學(xué)》2017年碩士論文

【摘要】：3D超高清電視的日益普及與發(fā)展帶動了人們對高幀率視頻的需求。幀率提升(Frame Rate Up-conversion,FRUC)作為一種獲取高幀率視頻且可實現(xiàn)視頻間幀率轉(zhuǎn)換的視頻后處理技術(shù),逐漸引起學(xué)術(shù)界的關(guān)注并成為研究熱點(diǎn)。幀率提升是一種利用連續(xù)兩幀之間的時域相關(guān)性獲得內(nèi)插幀,然后插入原始兩幀之間以達(dá)到增加幀率目的的技術(shù)。視頻的幀率越高,它的觀影效果也就越好,同時代表著畫面中的動作越流暢,細(xì)節(jié)越細(xì)膩。由于視頻幀率提升多樣化的應(yīng)用,FRUC技術(shù)在數(shù)字多媒體領(lǐng)域擁有廣泛的應(yīng)用前景,同時學(xué)術(shù)界也研究出了各種各樣的FRUC算法,其中應(yīng)用最為廣泛的是基于運(yùn)動補(bǔ)償?shù)腇RUC算法。該算法引入了運(yùn)動信息,可以很好地保證內(nèi)插幀處于原運(yùn)動軌跡上,但同時也會帶來一些問題,如塊效應(yīng)、模糊、遮擋等。本論文在2D視頻上展開研究,對基于塊匹配的運(yùn)動補(bǔ)償類幀率提升過程中的關(guān)鍵技術(shù):運(yùn)動估計、運(yùn)動矢量后處理和雙向運(yùn)動補(bǔ)償插幀做了深入的研究探討并提出有效可行的解決方案。論文的主要研究內(nèi)容可總結(jié)歸納為以下三點(diǎn):1.提出一種基于四重運(yùn)動矢量后處理的FRUC算法。通過采用混合運(yùn)動估計法即將前向、后向及雙向運(yùn)動估計相結(jié)合,避免遮擋和重疊等問題的發(fā)生;為了提高運(yùn)動矢量的精確性,前后向運(yùn)動矢量場的異常值將被檢測并通過基于先驗信息的修正算法對其進(jìn)行修正,然后采用矢量外插和加權(quán)求和的方法對雙向運(yùn)動矢量場進(jìn)行矢量平滑;此外,通過基于塊匹配率和階梯型策略的雙向運(yùn)動矢量選擇和判定方法實現(xiàn)單向矢量場向雙向矢量場的精確轉(zhuǎn)換。該算法可以提高運(yùn)動矢量的精確度,得到質(zhì)量高、效果好的內(nèi)插幀。2.提出一種基于時空域的自適應(yīng)運(yùn)動補(bǔ)償插幀算法。在運(yùn)動估計中加入預(yù)處理和紋理信息,既減少了計算量又提高了運(yùn)動矢量的精確度;然后對修正后的矢量進(jìn)行運(yùn)動分析,將其分為三種塊類型;最后對不同類型的塊基于時空域的精準(zhǔn)信息采用不同的補(bǔ)償插幀算法,最終得到高質(zhì)量的內(nèi)插幀,有效減少了塊效應(yīng)和模糊現(xiàn)象。3.在常見的二倍幀率提升基礎(chǔ)上,提出一種基于運(yùn)動信息的非整數(shù)倍FRUC算法,該算法可以實現(xiàn)任意分?jǐn)?shù)倍數(shù)的幀率上轉(zhuǎn)換。所提算法充分利用運(yùn)動信息選擇物體運(yùn)動最快的地方作為待插入幀的位置,并采用雙向運(yùn)動補(bǔ)償方法獲得該處的內(nèi)插幀,有效消除了幀率提升后的視頻中常見的模糊和運(yùn)動抖動現(xiàn)象。同時為了提高待插入幀位置判定的準(zhǔn)確性,該算法設(shè)計了基于幀間相關(guān)度和幀間運(yùn)動速度的插幀位置判定方法,并采用了新的場景檢測方法。該算法相對于其他傳統(tǒng)算法,提升后的視頻具有明顯的質(zhì)量改善,獲得較好的視覺效果。本論文提出的幀率提升方法經(jīng)過豐富的計算機(jī)仿真實驗和比較分析,結(jié)果表明,無論是在主觀視覺效果上,還是在峰值信噪比(Peak Signal to Noise Ratio,PSNR)和結(jié)構(gòu)相似度(Structural Similarity Index Measurement,SSIM)兩種客觀指標(biāo)上都優(yōu)于經(jīng)典的幀率提升方法。
[Abstract]:The increasing popularity and development of 3D ultra high definition television (HDTV) has led to the demand for high frame rate video. Frame rate upgrading (Frame Rate Up-conversion (FRUC)), as a video post-processing technology for obtaining high frame rate video and realizing frame rate conversion between video frames, has gradually attracted the attention of academic circles and became a hot topic. Frame rate promotion is a kind of use. The time domain correlation between the two frames is continuously interpolated and then inserted between the original two frames in order to increase the frame rate. The higher the frame rate of the video, the better its view effect, and the more smooth and delicate the movements in the picture. The FRUC technology is in digital media because of the diversification of the video frame rate. There is a wide range of application prospects in the field of body. At the same time, a variety of FRUC algorithms have been studied in the academic circle. The most widely used is the FRUC algorithm based on motion compensation. The algorithm introduces motion information, which can guarantee the interpolation frame to be on the original motion trajectory, but it also brings some problems, such as block effect, blurring, and obscure. In this paper, the research on 2D video is carried out. The key technologies in the frame rate improvement of motion compensation based on block matching: motion estimation, motion vector post-processing and bidirectional motion compensation interpolation are discussed and the effective and feasible solutions are proposed. The main contents of this paper can be summarized as following three points: 1. a FRUC algorithm based on four heavy motion vector post-processing is proposed. Through the combination of forward, backward and two-way motion estimation, a hybrid motion estimation method is used to avoid the occurrence of occlusion and overlap. In order to improve the accuracy of the motion vector, the anomaly value of the forward motion vector field will be detected and through the prior information. The correction algorithm is modified and the vector field is smoothed by vector extrapolation and weighted summation. In addition, an accurate transformation of one-way vector field to bidirectional vector field is realized by the method of two-way motion vector selection and decision based on block matching rate and step type strategy. The algorithm can improve the motion vector. The precision of quantity, high quality and effective interpolation frame.2. proposed an adaptive motion compensation interpolation algorithm based on space-time domain. In motion estimation, the preprocessing and texture information are added to the motion estimation, which reduces the computation and improves the accuracy of the motion vector. Then, the motion analysis of the corrected vector is divided into three kinds of block classes. Finally, we use different compensation interpolation algorithms for different types of block based accurate information based on space-time domain, and finally get high quality interpolation frames, which effectively reduces block effect and blurred phenomenon.3. on the basis of common two times frame rate lifting, and proposes a non integer multiple FRUC algorithm based on motion information. This algorithm can achieve arbitrary points. The proposed algorithm makes full use of the motion information to select the fastest motion of the object as the position of the frame to be inserted, and uses a two-way motion compensation method to obtain the interpolated frame of the object, effectively eliminating the common blurred and motion jitter in the video after the frame rate lifting. The algorithm designed the position determination method based on interframe correlation and inter frame speed, and adopted a new scene detection method. Compared with other traditional algorithms, the improved video has obvious quality improvement and better visual effect. The frame rate lifting method proposed in this paper has been proposed in this paper. The results show that both in the subjective visual effect, the two objective indexes of the peak signal to noise ratio (Peak Signal to Noise Ratio, PSNR) and the structural similarity (Structural Similarity Index Measurement, SSIM) are superior to the classic frame rate lifting methods.

【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 張麗曉;基于運(yùn)動補(bǔ)償?shù)囊曨l格式轉(zhuǎn)換算法研究[D];天津大學(xué);2009年

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本文編號：1888553