以區域式隨選品質的編碼進行長序列醫學影像的壓縮

日益增加的數位醫學影像序列資料量已產生傳輸與儲存的問題，透過一個適當的壓縮演算法可以有效降低問題的嚴重性。對於很長的醫學影像序列的有失真壓縮而言，在重建的影像中若能自動保存診斷的特徵的確是個不可或缺的需求。本論文提出一個以小波為基礎的自適性向量量化(AVQ)方法，此方法結合一個以失真臨界值來更新碼簿的機制(DCCR)，藉以達到使用者自訂的PSNR品質要求。在碼簿更新策略與眾所皆知的SPIHT編碼技術的巧妙搭配下，DCCR機制能提供優越的編碼增益。實驗結果顯示在編碼效能的表現上，所提出的方法優於單純的SPIHT與JPEG2000的演算法。此外，為了得到預設的品質需求，以能量品質曲線取替傳統的失真位元率曲線，提出一個遞迴式的快速估測演算法，並能平穩且可靠地進行品質控制。基於DCCR-AVQ在實際使用上會造成大量記憶體的消耗、初始碼簿訓練的費時與容易錯誤蔓延的情形等不利之處，加上醫學影像壓縮有從失真到無失真的任意形狀編碼的需求，因此，在本論文中進一步提出一個可以解決上述不利之處與符合上述需求的新方法。為了保有與DCCR機制可比擬的編碼效能，提出的方法在小波空間中以移動估測與移動補償的機制來取代碼簿搜尋與更新，以避免上述的缺點。再者，在具多物件或多區域重建的影像中，藉由本方法可以輕易且自動地分別達到醫護人員預設的失真或/及無失真的各種品質需求。經任意形狀的小波轉換(SA-DWT)後，DWT係數會依樹狀關係重組成若干個小波方塊(WB)。當具有任意形狀的多個區域被詳細標示後，使用者可以針對不同的區域指定對應的PSNR值。藉由DWT特性與失真分配策略的使用，像素空間的品質需求會以小波域上等價的失真值轉嫁到每個WB上。實驗結果顯示，所提出的方法能比傳統的SPIHT編碼方法有小很多的品質波動。對於有特定區域的長序列醫學影像壓縮，所提的方法在達到40與48 dB的目標PSNR值時，其最大的品質波動幅度分別只有7%與1%。對於任意種類的靜態影像與其中任意形狀的物件，所提出的品質控制方法仍然非常有效。此外，我們也展示了在同一影像的多個物件中，可以任意指定失真或/與無失真的品質控制能力。並且，也比較在SA-DWT的轉換中，使用不同的濾波係數組與架構的品質控制精準度。最後，提出的方法不但具有優於SPIHT的編碼效能，而且還能精確地保留物件形狀的邊緣。

關鍵字

自適性向量量化；失真限制的碼簿更新機制；區域式品質控制；形狀自適性的小波轉換； SPIHT ；醫學影像序列的壓縮；小波方塊

並列摘要

The enormous data of medical image sequences bring a transmission and storage problem that can be solved by using a compression technique. For the lossy compression of a very long medical image sequence, automatically maintaining the diagnosis features in reconstructed images is essential. In this dissertation, the proposed wavelet-based adaptive vector quantizer incorporates a distortion-constrained codebook replenishment (DCCR) mechanism to meet a user-defined quality demand in peak signal-to-noise ratio (PSNR). Combining a codebook updating strategy and the well-known SPIHT technique, the DCCR mechanism provides an excellent coding gain. Experimental results show that the proposed approach is superior to the pure SPIHT and the JPEG2000 algorithms in terms of coding performance. We also propose an iterative fast searching algorithm to find the desired signal quality along an energy-quality curve instead of a traditional rate-distortion curve. The algorithm performs the quality control quickly, smoothly, and reliably. Due to the disadvantages of using codebooks (high memory consumption, time-consuming initial codebook training, and serious error propagation) and the need of region-based coding with lossy-to-lossless functionality for medical image compression, we further propose a region-based compression approach for medical image sequences in this dissertation. To keep comparable coding performance with the DCCR mechanism, the new approach replaces codebook searching and DCCR by a motion estimation and compensation mechanism in wavelet coefficient domain to avoid the aforementioned disadvantages of using codebooks. Furthermore, the lossy and/or lossless quality levels of multiple regions in a decompressed image can be specified by a physician and achieved automatically by the proposed approach. After performing the shape-adaptive discrete wavelet transform (DWT), DWT coefficients arranged in hierarchical trees are grouped into wavelet blocks (WBs). The multiple regions with arbitrary shapes can be specified to have different assigned quality levels in terms of PSNR. The quality demand in pixel domain is converted to the equivalent distortion allowed for each WB in DWT domain via the use of DWT properties and a distortion assignment strategy. Experimental results show that the proposed approach has much smaller quality variation than the conventional SPIHT coding method. For image sequences with specific regions in each image, the proposed method achieves 40 and 48 dB target PSNR subject to the maximum quality variation of only 7% and 1%, respectively. For still images with arbitrarily shaped objects and various modalities, the quality control of the proposed method is still very effective. In addition, the performance of controlling lossy and/or lossless quality levels of multiple regions in one image is demonstrated and the quality controlling accuracy using SA-DWT with different filter banks is compared. Finally, the proposed approach not only performs better than SPIHT in coding performance, but also preserves the boundary and shape of the specified region accurately.

並列關鍵字

medical image sequence compression ； distortion-constrained codebook replenishment ； SA-DWT ； adaptive vector quantization ； Region-based quality control ； SPIHT ； wavelet block.

參考文獻

[1] Y. Kim and W. A. Pearlman, “Stripe-based SPIHT lossy compression of volumetric medical images for low memory usage and uniform reconstruction quality,” Proc. of Int. Conf. on Image Processing, vol. 3, pp. 652-655, 2000.

[2] S. Wong, L. Zaremba, D. Gooden, and H. K. Huang, “Radiologic image compression – a review,” Proc. of the IEEE, vol. 83, pp. 194-219, Feb. 1995.

[3] D. L. Gall, “MPEG: A video compression standard for multimedia applications,” Commun. of ACM, vol. 34, pp. 47-58, 1998.

[4] T. Wiegand, G. J. Sullivan, G. Bjntegaard, and A. Luthra, “Overview of the H.264/AVC video coding standard,” IEEE Trans. Circuits Syst. Video Technol., vol. 13, pp. 560-576, July 2003.

[5] B. Ho, M. Tsai, J. Wei, M. Ma, and P. Saipetch, “Video compression of coronary angiograms based on discrete wavelet transform with block classification,” IEEE Trans. Med. Imag., vol. 15, pp. 814-823, Dec. 1996.

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以區域式隨選品質的編碼進行長序列醫學影像的壓縮

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