本論文提出一個即時內視鏡系統應用於低功率無線身體感測網路，此系統主要包含三部份：可適應性低功率無線通訊協定與感測結點、筒狀失真影像校正器與高品質適應性影像縮放器。無線膠囊內視鏡是身體感測網路結點的一種，它從廣角鏡頭取得影像後透過一個適應性低功率無線通訊協定傳送至醫院的中央系統，由於所取得的影像經由廣角鏡造成失真，必需透過筒狀失真校正器校正影像；為了提供醫生高畫質影像進行診斷，校正後的低解析度影像需要被放大成高解析度影像。根據影像校正與縮放的高速需求，超大型積體電路被使用來實現應用於即時內視鏡系統中的影像校正器與縮放器。
校正器的電路架構基於最小平方法近似，硬體成本與記憶體需求減少藉由奇數級數近似、霍諾演算法、時間多工設計與線性內插簡化。影像縮放器是由一個新穎的演算法實現，它包含一個雙線性內插、一個鉗位濾波器與一個銳化空間濾波器；為了增加解決由雙線性內插所產生的模糊與混疊效應的能力，一個適應性技術被用來增進鉗位與銳化空間濾波器的效果；在超大型積體電路的實現上，為了減少記憶體緩衝器的使用，一個三乘三的鉗位濾波器和一個三乘三銳化空間濾波器結合成一個五乘五的迴旋濾波器，而雙線性內插電路由硬體共用技術簡少運算資源的使用。為了長時間無線身體感測網路的使用，可適應性低功率無線通訊協定與功率管理技術在本研究中被發展出來；再者，為了減少傳輸的資料量與能夠精準控制每部份功能電路的功率消耗，資料壓縮器與功率管理器被設計在每一個感測結點中；為了增進系統的效能，一個通訊週期與精準的管線化控制用來同步與操作整個無線身體感測網路。
影像校正器與縮放器的超大型積體電路架構分別包含13,900邏輯閘與92,800邏輯閘，與先前的技術相比，本論文所提出的影像校正器減少69%的硬體成本與75%的記億體需求，而本論文所提出的影像縮放器不僅減少46.6%的硬體成本，並且還增加至少0.42dB的影像品質；因此相較於由先前技術所組成的內視鏡系統，本論文所提出的系統可減少60.6%的硬體成本與74.9%的記憶體需求；最後，相較於一般沒有適應性低功率設計之無線通訊協定，本論文所提出適應性低功率設計可節省96.4%的功率消耗。

This thesis presents a real-time video-endoscopic system for a low power wireless body sensor network (WBSN). The proposed WBSN system consists of three parts, an adaptive low power wireless communication protocol and sensor nodes, a barrel distortion image corrector, and a high-quality adaptive image scalar. A wireless capsule endoscopy, which is one kind of sensor nodes, captures images with wide-angle lens and transmits the images to a central system by an adaptive low power wireless communication protocol. Since the captured image is distorted by wide-angle lens, it should be corrected by the barrel distortion image corrector. To be able to get high quality images for doctor diagnosis, the corrected images with low resolution are necessary to scale up with higher resolution. According to high speed demand for image correcting and scaling, the VLSI is used to implement the image corrector and scalar for real-time video-endoscopic system.
The VLSI architecture of the corrector is based on least-squares estimation. The hardware cost and memory requirement are reduced by an odd-order polynomial approximating, Hornor’s algorithm, time multiplexed design and a simplified linear interpolation. The scalar is implemented by a novel scaling algorithm which consists of bilinear interpolation, a clamp filter, and a sharpening spatial filter. To enhance the ability of solving the blurring and aliasing effects caused by the bilinear interpolation, an adaptive technique is used to improve the purposes of the clamp and sharpening spatial filters. To reduce memory buffers and computing resources for the VLSI implementation, a 3×3 clamp filter and a 3×3 sharpening spatial filters are combined into a 5×5 convolution filter. In addition, the bilinear interpolation is simplified by a hardware sharing technique. For long-time usage of the WBSN system, adaptive low power communication protocol and power management technique are developed. Furthermore, a data encoder and a power management are designed into each sensor node to decrease the transmission data rate and handle the power of each function accurately. To improve the system performance, a communication cycle is constructed to synchronize the WBSN with accurate pipeline control.
The VLSI architecture of the corrector or scalar contains 13.9-K gates or 9.28-K gates. As compared with previous techniques, the proposed corrector design reduces at lest 69 % hardware cost and 75 % memory requirement. The proposed scalar design not only decreases hardware cost by more than 46.6 % but also improves average quality of scaled image by 0.42 dB. Consequently, the proposed video endoscopic system reduces at least 60.6 % hardware cost and 74.9 % memory requirement than the system composed by previous works. Finally, comparing with communication protocol without adaptive low power design, the power consumption of proposed adaptive communication protocol with adaptive low power design is saved over 96.4 % as compared with the system without adaptive low power design for five various body sensor nodes application.

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