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研究生:管志偉
研究生(外文):Chih-Wei Kuan
論文名稱:利用logistic函數與Log-Gabor轉換進行影像融合之影像強化方法
論文名稱(外文):Image Enhancement Based on Fusion using Logistic Function and Log-Gabor Transform
指導教授:黃博惠黃博惠引用關係
指導教授(外文):Po-Whei Huang
口試委員:林芬蘭蔡孟勳張真誠徐麗蘋
口試委員(外文):Phen-Lan LinMeng-Hsiun TsaiChin-Chen ChangLi-pin Hsu
口試日期:2015-07-24
學位類別:碩士
校院名稱:國立中興大學
系所名稱:資訊科學與工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:英文
論文頁數:48
中文關鍵詞:影像強化影像直方圖影像融合邏輯斯特函數Log-Gabor 轉換
外文關鍵詞:Image enhancementImage histogramsImage fusionLogistic functionLog-Gabor wavelet transform
相關次數:
  • 被引用被引用:2
  • 點閱點閱:226
  • 評分評分:
  • 下載下載:53
  • 收藏至我的研究室書目清單書目收藏:0
影像強化方法可有效的改善或增強影像以提供人類更好的視覺或電腦更進階的影像處理工作。因此,強化過的影像往往會比原始影像更適合用於特定的應用面。傳統影像強化的方法一般存在著兩種常見的缺失。一個為對比度的減少,另一個為細節的遺失。除此之外,許多影像強化的方法在影像暗色區域都會產生不自然的點。在本論文中,我們提出兩階段式的影像強化方法,係利用影像融合策略來克服上述所說的缺失。於第一階段,利用影像直方圖壓縮以及擴展進行影像調整,以達到較少的非自然的點以及較好的對比度。第二階段,利用邏輯斯特函數與log-Gabor小波轉換之技術將原始影像與第一步驟調整後的影像進行融合。於多種典型影像的實驗結果,可說明我們的方法的確優於其他傳統影像強化方法,除了影像視覺外,在影像評比(Contrast、Entropy、Gradient)上也都有較好的數據表現。

Image enhancement methods are proposed to effectively improve or enhance images to provide new images with better perception for human viewers or advanced computer processing tasks. Therefore, the enhanced images are more suitable than the original images for a specific application. There existing two common deficiencies in traditional image enhancement methods. One is the loss of local contrast and another is the loss of details. In addition, many methods generate artifact points in the dark areas of their enhanced images. In this paper, we propose a two-stage enhancement method by image fusion strategy to overcome these deficiencies. In the first stage, image modification based on image histograms squeeze and expansion is conducted to obtain an image with less artifacts and better contrast. In the second stage, we combine the original image and the modified image obtained from the first stage by image fusion strategy based on logistic function and log-Gabor wavelet transform. Experimental results on several typical test images demonstrate the effectiveness as well as the outstanding performance of our method when comparing with other traditional methods in terms of contrast, entropy, and gradient. According to our experimental results, our method is a suitable and effective solution to the deficiencies of most image enhancement methods.

1. Introduction 1
1.1 Background 1
1.2 Objectives of the Thesis 5
1.3 Organization of the Thesis 7
2. Related Works 8
3. Image Enhancement Based on Fusion Strategy 15
3.1 General description of our method 15
3.2 Image modification 16
3.3 Image combination 22
3.3.1 Calculate local contrast by log-Gabor wavelet transform 23
3.3.2 Evaluate weight matrix 23
3.3.3 Combine images 23
4. Experimental results and analysis 24
4.1 Reducing artifacts in dark area of enhanced images 24
4.2 Improving loss of details in bright area of enhanced images 27
4.3 Performance comparison 30
5. Conclusions 43
Reference 45


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