面對行動平台的增加,目前主要的技術挑戰是如何提供有效的影像處理程式在資源有限的行動裝置。本論文為行動平台提出一個先進的影像處理技術。為了減少運算的複雜度,影像抽象化的過程會在雲端系統裡面處理。在這個技術,使用者擷取的圖片會被分析並偵測出visual attended的區域,這個區域接著會用來作為抽象化過程的可調適的細部保留區。為了要進一步減少行動裝置跟雲端系統之間傳輸的影像大小並保留抽象化圖片的影像品質,本研究使用Attended Region的區域作為Sparse Coding的Dictionary,用以壓縮輸出資料的Attended區域,結果在效能需求之內解決了問題。
Given the increasing number of mobile platforms, a key technical challenge is how to provide efficient image processing application on resource-limited mobile devices. This paper proposes a novel technique for mobile image abstraction on mobile platform. In order to reduce the computation complexity, the image abstraction process is conducted on a cloud computing system. In this technique, captured images are analyzed to detect visual salient area, which is then provided for adaptive detail preservation of abstraction. To further reduce the image size for efficient transmission between mobile device and cloud computing system while maintaining the visual quality of abstracted image, the derived algorithm regards the salient regions as the dictionary in sparse representation, and selects the salient regions that minimize the residual output error iteratively, thus the resulting regions have a direct correspondence to the performance requirements of the given problem.