顏文明臺灣大學：資訊工程學研究所劉耀文Liu, Yau-WenYau-WenLiu2007-11-262018-07-052007-11-262018-07-052006http://ntur.lib.ntu.edu.tw//handle/246246/53913本篇論文提出了一個植基於空間域與頻率域的高灰階影像表示法，其影像表示法分為兩個階段，在第一階段，當特定的誤差容忍度被指定時，根據二分樹的分解原則，S樹空間資料結構被用來表示輸入灰階影像的二分樹結構，在建置好的S樹空間資料結構裡，子葉節點被劃分成兩個類型，那就是同質子葉節點與非同質子葉節點，其中同質子葉節點被用來表示一個正方形或長方形的平滑(低頻)子影像，而非同質子葉節點則被用來表示一個不平滑(高頻)子影像；在第二階段，每一個非同質性的子葉節點都被植基於離散餘弦轉換的編碼機制進行編碼以便降低記憶體的需求量。根據一些真實的高灰階影像，實驗結果證明我們提出的高灰階影像表示法相較於之前一個已經被發表的影像表示法有著大約平均63%的記憶體節省提昇率，最後我們發展一個可以在我們影像表示法上直接作動差運算的壓縮式計算，保留了空間資料結構可以作壓縮式運算的特性。In this thesis, a novel hybrid gray image representation using spatial- and DCT-based approach is presented. In the first phase, according to the bintree decomposition principle under the specifed error, an S-tree spatial data structure (SDS) is used to represent the decomposed bintree of the input gray image. In the constructed S-tree SDS, the leaves are partitioned into two types, namely the homogeneous leaves and the nonhomogeneous leaves. The homogeneous leaf is used to represent one rectangular or square homogeneous subimage with smooth, i.e. low frequency, content and the nonhomogeneous leaf is used to represent one nonhomogeneous subimage with nonsmooth, i.e. high frequency, content. In the second phase, each nonhomogeneous leaf is encoded by the DCT-based coding scheme for reducing the memory requirement. Based on some real gray images, experimental results show that our proposed gray image representation over the previously published S-tree- and shading-based SDS has about 63% memory-saving improvement ratio in average. Finally, we investigate the computational benefit when computing moments on our proposed gray image representation directly.1 Introduction .......................................... 1 2 Past Work: STC-based SDS for Representing Gray Images and Its Shortcoming ..................................... 3 3 The Proposed SDCT-based Gray Image Representation ..... 9 4 Application: SDCT-based Moment Computation ............16 5 Experimental Results ..................................21 5.1 Performance comparison between the proposed SDCT-based representation and the previous STC-based one ...........21 5.2 Application: moment computation .....................25 6 Conclusions ...........................................27 A The Proof of Lemma 1 ..................................28850203 bytesapplication/pdfen-US影像壓縮離散餘弦轉換灰階影像表示法線性插補動差計算空間資料結構DCTGray image representationLinear interpolationMoment computationSpatial data structurethesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/53913/1/ntu-95-R93922015-1.pdf