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博碩士論文 etd-0627116-230604 詳細資訊
Title page for etd-0627116-230604
論文名稱
Title
影像處理電路之低成本可靠度評估與分級方法及其硬體實現
A Low-Cost Dependability Evaluation and Grading Method and Its Hardware Implementation for Image Processing Circuits
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
71
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2016-06-30
繳交日期
Date of Submission
2016-07-28
關鍵字
Keywords
影像處理電路、可信賴度、品質評估、容誤、FSIMc
dependability, error-tolerance, quality evaluation, FSIMc, image processing circuits
統計
Statistics
本論文已被瀏覽 5649 次,被下載 23
The thesis/dissertation has been browsed 5649 times, has been downloaded 23 times.
中文摘要
隨著科技越來越進步,車用電子與物聯網(Internet of Things)已成為電子系統發展趨勢。對於這些系統而言,影像處理電路為一關鍵元件,例如行人辨識、車道辨識等已逐漸成為標準配備。此電路之可靠度也因此極需測試,以確保這些電子系統之可靠度,乃至於其應用之安全性。
容誤為近幾年來所提出之嶄新觀念,其主要評估當晶片出現運算錯誤時錯誤之可接受度,以提升晶片之有效良率與使用壽命。在錯誤仍可接受的情況下,晶片則可繼續使用。在此論文中,我們利用容誤評估影像處理電路出現運算錯誤時之可接受度並進行分級。分級結果也將適時用來警告使用者,讓使用者了解錯誤之嚴重性,以決定接下來的作為,例如繼續使用以節省成本,或是須立刻進行修復。
本論文採用目前可見與人類視覺感受最為相近的FSIMc影像品質評估參數,以檢視我們所提出方法之準確度。我們也考慮了多種可能出現之錯誤,包含因老化效應可能造成之單一固接錯誤與多重固接錯誤,以及因高溫與電源切換所容易造成的高斯雜訊與胡椒鹽雜訊。與過去影像品質評估方法相比,我們所提出之方法更容易以硬體電路實現,以更快速準確決定影像之可接受度,且所需成本極低。影像晶片不僅可藉此方法區分為可接受與不可接受,更能進一步分級為高品質、一般品質與低品質。透過使用大量有錯影像進行驗證,與FSIMc相比我們所提出方法之分級準確度可達96.16%。值得一提的是,我們的方法適用於各式輸出格式之影像處理電路,例如輸出灰階影像格式,或是紅、綠或藍 (RGB)影像格式。我們也將我們所提方法進行硬體驗證,結果顯示此硬體可輕易與商用JPEG解碼器達到相同操作頻率,達到即時影像品質評估,且所需額外面積成本僅為商用JPEG解碼器之5%以下。
Abstract
Image processing circuits are expected to be widely used in IoT (Internet of Things) and automotive electronics. For these applications, dependability evaluation is critical. In recent years error-tolerance has been proposed as a new way to extend lifetime of chips. The acceptability of errors produced by defective or aged chips are carefully examined, and if there exist only acceptable errors, the chips are likely to be still functional. In this thesis, we focus on the utilizing error-tolerance to evaluate dependability of image processing circuits. By analyzing the acceptability of the generated images to grade target circuits, users can be warned and take proper actions. To evaluate the accuracy of our method, we employ the image quality accessment attribute of FSIMc as basis. FSIMc has been shown to be able to reflect human visual system (HVS) the most accurately among the developed attributes so far. A large number of potential errors that may appear due to wear-out/aging during in-field use of a target system are considered, including sigle/ multiple stuck-at faults and two types of common noises, including Gaussian noises and salt-and-pepper noises. Compared with previous work, our method is easiler to implement and more efficiently evaluate acceptability of images. The experimental results for a large number of erroneous images show that our test method can achieve the accuracy of 96.16%. Moreover, our method is applicable for circuits that output different color formats of images such as gray scale or RGB. We have also implemented the proposed method by hardware. The results show that the hardware can work with the same operating frequency of the commercial JPEG decoder. Thus real-time acceptability evaluation can be achieved. The hardware implementation results also show that the required area overhead is only 5%.
目次 Table of Contents
論文審定書 i
誌謝 ii
摘要 iii
Abstract iv
目錄 v
圖目錄 vii
表目錄 ix
第一章 概論 1
1.1 論文背景與動機 1
1.2 研究貢獻 2
1.3 論文大綱 4
第二章 研究背景與文獻回顧 5
2.1 影像評估參數與複雜度評估 5
2.1.1 Structural Similarity (SSIM) 5
2.1.2 Feature SIMilarity(FSIMc) 6
2.1.3 FSIMc與SSIM複雜度分析 8
2.2 JPEG2000 9
2.3 錯誤模型 10
2.3.1 單一錯誤/多重錯誤(Single S-a Fault/Multiple S-a Faults) 10
2.3.2 高斯雜訊(Gaussian Noises) 13
2.3.3 胡椒鹽雜訊(Pepper & Salt Noise) 14
2.3.4 錯誤模型特徵分析 15
2.4 影像錯誤效應 16
2.4.1 Blocking Effects 16
2.4.2 Darkened/Brightened Effects 17
2.5 頻率導向之影像可接受度評估方法 17
2.5.1 影像頻率萃取方法 18
第三章 高效率分級影像處理電路之方法 20
3.1 簡介 20
3.2 參數分析 22
3.2.1 DiffTH數值之決定 22
3.2.2 亮暗點數值定義與決定數量臨界值 27
3.2.3 PPR下界臨界值之決定 29
3.2.4 影像電路可接受度評估流程 29
3.2.5 不同DiffTH數值與FSIMc準確度分析 31
3.2.6 不同PPR下界與FSIMc準確度分析 32
3.2.7 RGB Channel 準確度 35
3.2.8 影像電路分級 39
3.2.9 10張測試影像評估影像處理電路 40
3.2.10 動態測試影像 42
第四章 硬體電路實現與結果討論 47
4.1 分級影像處理電路之方法硬體實現目標 47
4.1.1 頻率 47
4.1.2 面積 47
4.1.3 功率消耗 47
4.2 頻率導向的影像品質評估參數之電路品質評估方法硬體實現 48
4.2.1 硬體架構-靜態 48
4.2.2 硬體實現結果 49
4.2.3 硬體架構-動態 50
4.2.4 硬體實現結果 51
4.2.5 結果與討論 52
第五章 MTTF 53
第六章 結論與未來展望 57
參考文獻 58
參考文獻 References
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