複合式分散式影像編碼之演算法及硬體架構設計

隨著物聯網路以及無線感測網路的蓬勃發展，能夠達到低功耗以及低成本的無線感測裝置在應用端上扮演著非常重要的角色。現有的影像壓縮技術，例如MPEG以及H.26x，在壓縮效果上比起以前進步不少，能夠達到很好的壓縮率。但是為了要把影像中重複的資訊給壓縮掉，就必須要做非常多分析的動作，例如動作的估測。這類的壓縮器必須得耗費大量的硬體以及運算量來達到良好的壓縮效果，但卻付出了高功耗的代價，雖然非常適合應用在傳統廣播系統上，但是在物聯網的應用層面上則是無法達到其低功耗的需求。分散式影像壓縮技術是近年來興起的影像壓縮技術，提供了一個具前瞻性的貢獻，他能讓壓縮器的成本大幅度的下降，而且在耗電上也能達到低功耗的需求，非常適合應用在物聯網的系統中。雖然分散式影像壓縮技術有如此優點，但是在壓縮效率上跟傳統的影像壓縮技術還有非常大的差距，在這裡我們提出了一個複合式架構將傳統的壓縮技術整合進來，並且設計一套可以動態選擇適合的壓縮方式的硬體，實驗結果顯示比起前人的分散式影像壓縮器的架構，我們可以達到更好的效果，同時運算的複雜度只有些微的上升(0.37%)，依舊維持了此一壓縮器低複雜度的優勢。在硬體實做方面，我們設計了一套可以大幅度增加運算效能的硬體，其中我們也大幅減少了在原先軟體架構中所需要的暫存記憶體(減少了75%)，其中LDPC的長度大小從6336被縮減到1584。最後我們所設計的硬體能夠處理到4CIF(704x576) 60fps的影像，並且在功耗上只耗了5.17mW。

關鍵字

影像壓縮；影像編碼

並列摘要

Low-power and low-cost distributed wireless video sensors play important roles for applications in machine-to-machine (M2M) and wireless sensor networks. Conventional video coding standard, i.e. MPEG and H.26x, offers tens of to hundreds of compression ratio and has improves the coding efficiency a lot better than before. Although the correlation between frames is well exploited on this hybrid coding structure, the power consumption is usually large at the encoder side mainly because of the high complexity of motion estimation. This kind of video coding systems are suitable for broadcasting but does not meet the requirements of M2M or wireless sensor networks due to limited hardware resources of the sensor nodes. Distributed video coding (DVC), a new video coding paradigm which is based on Slepian-Wolf and Wyner-Ziv theories, provides a promising solution for implementing low-power and low-cost distributed wireless video sensors since most of the computation load is moved from the encoder to the decoder. It has been showed that there is still room to improve the coding efficiency of the current DVC codec. In this work, we propose a hybrid coding structure with framelevel coding mode selection (CMS) to allow the DVC encoder to flexibly choose channel coding or entropy coding to code each band. The experimental results show the significant improvement on the rate-distortion (R-D) performance (up to 6dB gain in PSNR compared to the DISCOVER codec when the GOP size is 8) with only slight increase in the encoding complexity compared to the DISCOVER codec, which the runtime is increased 0.37% for software simulation. The proposed DVC system performs comparably to H.264 No Motion with much lower encoding complexity. For the hardware implementation, we proposed a 4-stage block-based pipeline Wyner-Ziv encoder, which increases the overall throughput. Plus, we remove the frame buffer for quantization stage and channel coding stage which is required in the original DVC codec. The code length of LDPC encoder is reduced from 6336 to 1584, which makes the size of internal SRAM much smaller (75% reduction). The design is implemented with TSMC90nm technology. The processing capability is 4CIF(704 576) with 60 frame per second.

並列關鍵字

Distributed Video Coding

參考文獻

[1] T. Wiegand, G.J. Sullivan, G. Bjontegaard, and A. Luthra, “Overview of the H.264/AVC video coding standard,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, no. 7, pp. 560–576, July 2003.

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[2] B. Girod, A.M. Aaron, S. Rane, and D. Rebollo-Monedero, “Distributed video coding,” Proceedings of the IEEE, vol. 93, no. 1, pp. 71–83, Jan. 2005.

Google Scholar

[3] J. Ascenso, C. Brites, and F. Pereira, “Improving frame interpolation with spatial motion smoothing for pixel domain distributed video coding,” in Proc. 5th EURASIP Conf. on Speech and Image Processing, Multimedia Communications and Services, 2007.

Google Scholar

[4] C.-C. Chiu, S.-Y. Chien, C.-H. Lee, V. S. Somayazulu, and Y.-K. Chen, “Distributed video coding: a promising solution for distributed wireless video sensors or not?,” in Proc. Visual Communications and Image Processing (VCIP), Nov. 2011.

Google Scholar

[5] “ITU Internet reports 2005: The Internet of Things,”.

Google Scholar

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複合式分散式影像編碼之演算法及硬體架構設計

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