醫療器材檢測系統之實時運動圖像模糊移除

Abstract

本論文提出一個基於雙離散小波轉換即時重建動態模糊影像的方法。將模糊圖像透過兩次小波轉換後，能夠清楚的觀測出清晰圖像與模糊尺度並藉以修正。在本論文中，我們利用Zhang所提出的雙小波轉換 (Double Discrete Wavelet Transform) 出發，利用自相關 (Auto-correlation) 的與登山式搜尋法 (Hill Climbing Algorithm) 方式估測模糊尺度。並利用估測出的尺度資訊推測真實圖像高頻訊號。實驗結果顯示我們提出的方法與其餘方法相較下有較快的執行速度並能即時執行。 處理速度可達30張/秒，可用於即時系統中。

Motion blur is a common phenomenon in photography. Blur may render the image useless and lead to inaccurate result. In many inspection industries, blur will cause large error and cannot be ignored. In this thesis, we propose a real-time method to improve motion blur for the medical capsule defect inspection system. We simplify the problem of dealing with motion blur with constant velocity k and moving horizontally. Based on double Haar wavelet transform, we estimate the length of blur kernel with auto-correlation and hill climbing searching algorithm. With the information of blur kernel, we are able to correct the proper coefficients in wavelet domain iteratively. We compare the deblur results and execution time of previous work and our method and achieve satisfactory results.