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Computational Photography Final project – D eblur

Computational Photography Final project – D eblur. 601415004 巫承熹. Background. In photography, it have different type of blur Camera shake( 相機晃動 ) User moving hands Scene motion( 場景位移 ) Objects in the scene moving Defocus blur ( 失焦 ) Depth of field effect.

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Computational Photography Final project – D eblur

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  1. Computational Photography Final project – Deblur 601415004 巫承熹

  2. Background In photography, it have different type of blur • Camera shake(相機晃動) • User moving hands • Scene motion(場景位移) • Objects in the scene moving • Defocus blur (失焦) • Depth of field effect Prof. Shing-Min Liu, Computational Photography: Applied Graphics and Imaging course lecture(2013)

  3. Introduction 在拍照攝影時，有上述幾種造成影像模糊的原因。其中，相機的晃動，可以藉由裝設感應器(如：加速度計、陀螺儀)來擷取移動向量，以解決模糊。這類的去模糊方法已經廣泛的被應用在相機的光學防手震(OIS)上。 HTC官方網站, http://www.htc.com/tw/zoe/stabilization/

  4. Introduction 然而，場景(物件)的位移卻無法直接由相機上的感應器直接的量測，因此，在這裡我們試著用基本原理，去除場景(物件)的簡單位移造成的模糊。

  5. Estimation the Degradation Function Give the blur source image: We try to recover the image using estimation the degradation funtion g(x,y) = f(x,y) * h(x,y) (1) G(u,v) =F(u,v) * H(u,v) (2)

  6. Method Step1: Load the blur source image , then convert it to the frequency domain using FFT. Get . Step2: Calculate , in frequency domain. In this case, we only have horizontal motion, therefore, , which , and a is parameter between 0.11 to 0.15. Step3: for avoiding case of “division zero”, we set a threshold , which is a small positive constant. If , then let , otherwise, . Step4: Use inverse FFT to convert from frequency domain to spatial domain .

  7. Flow Cart Load Image File FFT Inverse FFT Display

  8. User Interface ( Qt ) QT是一個跨平台的C++應用程式開發框架，被廣泛的應用於開發GUI程式。選擇使用這個GUI的介面，除了他擁有影像處理能力，還有因為它的支援跨平台的特性。這使我們可以將程式移植至嵌入式平台上執行，以提升系統攜帶的方便性與實用性。

  9. User Interface Load Image file (.bmp only) Source Image Display here Result Image Display here Set the parameter Click the button to display reult

  10. Result 因為每個來源影像的blur kernel 是未知的，因此根據不同的來源影像，會有不同的最佳輸入參數。 a=0.14 a=0.11

  11. Result 然而，並不是每個case都可以成功地找到參數，使圖片去模糊。在這個case中，圖片經過轉換產生的許多雜訊。但雖然如此，但是車子的下半部分仍然成功地去模糊。 DemoVideo( Youtube,Demo.avi) a=0.156

  12. 結論 在照相越來流行的時代，Deblur是非常實用的領域，目前市面上利用OIS解決相機晃動的作法已是非常普及，然而拍攝物體的移動是未知的，因此，我們運用預測DegradationFunction的方式來去除模糊。 目前我們以手動調整參數來實現。未來，可以利用一些設定參數的策略，來完善這個研究。

  13. Reference [1] Prof. Shing-Min Liu, Computational Photography: Applied Graphics and Imaging course lecture(2013)  [2] HTC官方網站, http://www.htc.com/tw/zoe/stabilization/ [3]Wikipedia, http://zh.wikipedia.org/zh-hant/Qt [4]M. Ben-Ezra and S. K. Nayar  "Motion-based motion deblurring",  IEEE Trans. Pattern Anal. Mach. Intell.,  vol. 26,  no. 6,  pp.689 -698 2004 

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