研究生: |
張思敏 Sih-Min Jhang |
---|---|
論文名稱: |
基於自身相似性的多比例因子影像及視訊超解析 Image and Video Super-Resolution based on Mutli-Scale Local Self-Similarity |
指導教授: |
楊傳凱
Chuan-kai Yang |
口試委員: |
花凱龍
Kai-Lung Hua 孫沛立 Pei-Li Sun |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 資訊管理系 Department of Information Management |
論文出版年: | 2015 |
畢業學年度: | 103 |
語文別: | 中文 |
論文頁數: | 45 |
中文關鍵詞: | 影像超解析 、視訊超解析 、自我相似性 、金字塔模型 、混合式鏡頭 |
外文關鍵詞: | Self-Similarity, Pyramid Model, Hybrid-cameras |
相關次數: | 點閱:294 下載:1 |
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在科技的快速進步下,人們對於真實感的需求更加提升,但生活周遭還是充滿了許多低解析度的視訊,而視訊超解析(Super Resolution, SR)能夠將這些低階析度的影像提升到高解析度影像。
現有的攝影器材提供了錄影同時拍照的功能,於是我們提出了一個超解析度的架構,我們利用較高解析度的影像加入到視訊超解析當中,透過影像自我相似性對視訊每個幀(Frame)進行超解析,並使用金字塔架構及二元搜尋法來加速補丁匹配運算。
系統提供使用者將欲超解析的視訊作為輸入,系統將透過影像的自我相似性來補償原視訊不足的部分,以提升視訊之畫質,達到高解析度的輸出結果。
Because of the advances in Science and technology, people are more used to realistic things, but there are still a lot of low-resolution images and videos around the world, so we need the Super Resolution technique to improve the quality.
Nowadays, Hybrid-cameras have been invented, and therefore we propose a new technique that extends existing example-based super-resolution frameworks, by considering the embedded external high definition images for video super resolution, together with the property of local self-similarity. For the efficacy of patch matching, we use a pyramid model and binary search method to find the matching window quickly and reduce comparison time.
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