基於低複雜度和高效能考量之內容調適性解交錯設計

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姓名

林學良(Hsueh-Liang Lin) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

基於低複雜度和高效能考量之內容調適性解交錯設計
(A Content Adaptive De-interlacing Design with Low Complexity and High Performance Considerations)

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摘要(中)

解交錯的技術是將交錯的影像轉換成循序掃描的方式，這技術被使用於液晶電視，循序掃描類比電視，和背投影電視等。在過去的幾年，在這領域有很多研究文獻被提出。其中最熱門的方法是動像調適性解交錯法。這個方法的優點在於它的運算量不大，而且容易硬體實現，並被現今多數產品所採用。假設你想提升這個方法所得到的影像品質，有不少的研究提出利用動態補償的方法去取代動像調適性解交錯法中的圖場間內插法。雖然動態補償法可以得到更好的影像品質，但是它所需要的運算量，還有硬體的花費都是你所在意的。為了去降低動態補償法所帶來的高複雜度的運算量，我們提出了區塊模式決定的機制去區分這個區域的點是屬於動態的點，邊緣的點或是動態補償的點。由於我們使用區塊模式決定這機制，我們可以避免在一些不適用動態補償法的區域去使用它。而且經由區塊模式決定機制的選擇，我們可以在最適合的點用最適合的內插法去做插入的動作.不像動像調適性解交錯法，當影像輸入時，對於每個輸入點都同時去做了圖場內內插法和圖場間內插法的動作，在影像輸出前才去決定用那一種內插法。跟先前所提出的演算法相比，我們的演算法不但可以降低運算的複雜度，更可以對影像品質有所提升。我們更使用ATEME公司所推出的IEKC64x的模擬平台去做演算法的模擬。藉此，我們可以證明我們演算法是低運算量的。在實驗的結果上，我們可以發現我們的演算法大概可以節省接近80%的運算量又可以得到更好的影像品質。

摘要(英)

De-interlacing converts interlaced video sequences into progressive ones for displaying on progressive devices such as LCD, Progressive CRT, and Projection TV. In previous years, many de-interlacing algorithms are published. The most popular de-interlacing algorithm of them is motion adaptive (MA) method. The advantage of this method is low computational complexity and easy to implement in many products. If you want to get better video quality by using MA method, many searches find: using motion compensation (MC) method to replace the inter-field method of MA method is a good solution. Although MC method can get better video quality, the main concerns of MC method are computational complexity and hardware cost. In order to reduce the computational complexity of MC method, we attempt to use block type decision to distinguish the pixel into stationary, texture, and MC pixel which can help us to avoid us MC method for non-adaptive area. Base on the type of the pixel, we can use the most adaptive interpolation method for every pixel. Not as MA method, when video sequence inputs, every pixel is interpolated by intra-field and inter-field method. Compare to other de-interlacing algorithms, our proposed algorithm not only has low computational complexity but also gets better video quality. We use IEKC64x platform for real time simulation to proof our proposed algorithm is low complexity. Experimental result shows that the proposed algorithm can save nearly 80% computational power and get better video quality.

關鍵字(中)

★ 解交錯

關鍵字(英)

★ deinterlace
★ deinterlaing

論文目次

Content………………………………………………………………………………... i
List of Figures………………………………………………………………………..iii
List of Tables…………………………………………………………………………. v
Chapter 1 Introduction………………………………………………………….. 1
1.1 Introduction…………………………………………………………....2
1.2 Thesis Organization………………………………………………….... 4
Chapter 2 Related Works on De-interlace Design...……………………………5
2.1 Intra-Field Method………….………………………………………… 6
2.2 Inter-Field Method…….……………………………………………… 8
2.3 Motion Adaptive Method……...……………………………………… 8
2.4 Design Issues on Computation and Performance…...…………….... 12
2.4.1 The Drawbacks of Intra-Field Method………………………... 12
2.4.2 The Drawbacks of MA Method……………………………...... 13
Chapter 3 Proposed De-interlacing Algorithm……………………………….. 14
3.1 Limitations on MC Method……..…………………………………... 15
3.1.1 Field Boundary……..……………………..…………………... 15
3.1.2 Stationary or Background Area……..………………………… 16
3.1.3 Texture Area or Object Boundary……..………………………. 16
3.1.4 Scene Change Field……..…………………………………….. 17
3.2 Proposed Algorithm………………………..………………………... 18
3.2.1 Edge-base Adaptive Weight Average (EAWA)…..…………... 18
3.2.2 Two-Field Motion Compensation Method…….……………... 22
3.2.3 Previous Field Insert…….…………………………………..... 23
3.2.4 Block Type Decision…….…………………………………..... 23
3.2.5 Flow Chart of Our Proposed Algorithm…….……………….... 29
Chapter 4 Experimental Result and Analysis………………………………… 31
4.1 Analysis of Computation Complexity……………………………….. 32
4.2 Subject View and PSNR Comparison..……………………………… 33
Chapter 5 DSP Realization of Our Proposed Algorithm.……………………. 40
5.1 Introduction to ATEME IEKC64x Platform………………………… 41
5.2 Implement Our Proposed Algorithm……………………………….. 42
5.2.1 Simulation Environment…………………………………….... 42
5.2.2 How to Implement Our Proposed Algorithm on ATEME IEKC64x Platform…………………………………………….. 43
Chapter 6 Conclusions………………………………………………………….46
Reference……………………………………………………………………………. 48

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指導教授

蔡宗漢(Tsung-Han Tsai)

審核日期

2006-10-30

推文