應用於高階液晶顯示器之高品質畫面更新率提升轉換技術
為了解決多媒體裝置間大量的連接線路，因此多種家用無線傳輸系統被提出，如wireless HD或者WHDI等。然而現有無線傳輸系統主要專注於點對點高速數據傳輸，而且關於傳輸距離部分也有嚴格限制，因此在使用上會有需多限制。因此一個整合網路機制、無線傳輸、以及多媒體壓縮之系統被提出，稱之為WHDVIm。在此系統中有兩個重要模組，分別為畫面更新率提昇技術以及可延伸編解碼。
High Visual
Quality Particle Based Frame Rate Up Conversion With
Acceleration Assisted Motion Trajectory Calibration
首先在基於粒子特性之畫面更新率提昇技術中，此論文藉由多階層動態估測以及基於粒子特性之軌跡校正來產生所需之內插影像。另外除了利用軌跡與現有內插方塊之距離外，第一階段產生之絕對誤差和與第二階段產生之雙向絕對誤差和亦聯合考量用以最小化誤差。根據實驗結果，本提出之演算法比起現有演算法，其畫質高出0.9~3.9 dB，其中所包含之比較對象包含單項估測以及雙向估測之演算法。此實驗結果證實使用單項動態估測所得到之動態向量比起雙向估測更為精準。另外也證實基於軌跡之動態估測也能有效的選擇正確動態。
接下來在混合型畫面更新率提昇技術(Hybrid FRUC)中，將動態估測衡量標準做進一步的強化，用以加強原來基於例子特性之畫面更新率提昇技術中之第二階段，也就是軌跡取得部份。另外，原始演算法中重複運算利用記憶體存取的方式化簡，讓執行時間更加快速。最後更在大尺寸畫面中使用較大的搜尋方塊。加大大畫面之搜尋方塊不但畫質不會下降，且複雜度會急遽降低。由實驗結果發現，其畫質比起現有方法高出0.3 dB以上，而且複雜度降低了29~90%，可以證實此演算法之效率以及畫面提昇的效果。
DEMO Video
Flower
Video
Football
Video
mobile
Video
Hierachical MV field Flowchart
Motion trajectory calibration stage (PMTC)
Flowchart
PSNR Result
Accurate Frame Rate Up-Conversion for Advanced Visual Quality(AFRUC)
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l a motion compensated FRUC algorithm is proposed, which is able to acquire more accurate motion vectors by referencing neighboring frames with hierarchical motion filed construction block size and an MV mapping stage.
l The block size of hierarchical MV filed construction has been enlarged in order to acquire more motion information, and the size of the MV mapping and image interpolation stage has been reduced to obtain a more accurate interpolated result.
l In order to smooth the motion vector, a median filter is considered with SAD (sum of absolute difference) value and constructed with an adaptive motion vector smoothing method.
l For the purpose of suppressing the debris, a noise removal filter is applied after the interpolation operation.
l According to the experimental result, the proposed approach is able to improve visual quality performance by 0.82 dB on average. Subjective analysis shows that annoying artifacts are significantly reduced.
The overall flowchart of Accurate Frame Rate Up-Conversion
AFRUC Result
Fig. The snapshot of Silent on frame no. 73 with (a) the original video, (b) PFRUC, (c) extend BME, (d) Multiple Hypotheses Bayesian FRUC, and (e) AFRUC
PSNR Result
TABLE THE EXPERIMENTAL RESULT BY PSNR
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