| 摘要: | 紅外線影像尋標系統 (IIR) 前瞻技術研究的影像融合技術為二年期的研究計畫 (原為三年期計畫縮短為二年)。研究主題為：第一年發展可見光影像與紅外線影像的融合技術，比較空間域與頻率域影像融合技術的優劣，並實做以小波為基礎的影像融合法則。本年度計畫是第二年，發展上述光學影像與3 ~ 5 m 中波長紅外線影像的融合技術，並發展上述融合影像後的目標特徵辨識。影像融合的目的是將多張有相關性但具有不同內涵 (content) 的影像融合在一起，將各種內涵同時呈現在一張影像中，讓下一步驟的判斷與分析能夠有更多資訊的支援而得到更正確的結果。影像融合技術有很多種，最基本的方法是高通濾波法 (high-pass filtering method)；最近熱門的方法有：以小波轉換 (DWT) 為基礎的方法、均勻理性濾波法 (uniform rational filter bank)、及拉普拉斯金字塔結構法 (Laplacian pyramid)。影像融合技術的應用方式有：不同時間相同地點相同性質影像的融合、相同地點不同解析度的影像融合、不同感測器的影像融合、部份重疊地點的影像融合、.. 等。不同影像融合的應用，其研究重點也有所不同。例如，有些應用是要從多頻譜影像中的頻譜資料做地表材質 (material) 的分析；因此這樣應用的研究重點在於不破壞原始影像的頻譜資訊 (spectral information)。另外如醫學影像、不同解析度影像、及不同清晰度影像的融合應用，其主要目的是提供人眼觀看；因此這些應用不在乎頻譜資料的改變，只在乎能否保持各自完整的資訊。經由上述融合後的影像可以提供給我們更多資訊，以利後續的判斷與分析。而本研究的最終目的即是就上述的融合影像執行目標特徵辨識。目標辨識的意義是以空載飛機上的可見光影像與中波段的被動式紅外線影像融合；最後就融合後的影像執行地面目標辦識。中波段紅外線影像資料較不易取得，因此計畫中會以一般空載紅外線影像代替中波段紅外線影像。過去十多年來，我們一直都在從事衛星影像處理、地形景觀分析、及 3D 地理資訊系統相關的研究。已完成與本計畫相關的技術有：利用馬可夫隨機場做多光譜遙測影像分割、非督導式多頻譜遙測影像紋理分割、以多頻譜遙測影像合成紅外線影像景觀、多頻譜影像融合與紅外線影像合成、以關聯隱藏馬可夫樹模式做多重解析度紋理分割、以多時段的 SPOT 衛星影像做雲層自動去除等。在第一年度計畫中，我們也實做了: (i) 影像定位校正方法 及 (ii) IHS-based, PCA-based, and wavelet-selection-based 等影像融合方法；因此我們有信心來完成本計畫的執行。 This study of target detection in infrared images is a two-year research project. The studying topics of the two years are described as follows, respectively. (i) In the first year, we will develop the image fusion techniques for visible-spectral and infrared images. At least, we will implement a wavelet-based image fusion method. We will also survey and compare the spatial-domain and frequency-based fusion methods to provide the useful comments. (ii) This is the second year, in this year, we study and survey the properties of 3 ~ 5 m wave-length infrared images, develop the image fusion algorithm for visible and infrared images, and then develop the target detection algorithms for the fused images. The purpose of image fusion is to combine several related but having different content images into an image such that all the contents can be appeared in one single image to benefit the following processing and analysis. There are many different kinds of image fusion methods. The most famous method is the high-pass filtering method; the most hot methods include the wavelet-based fusion method, the methods based on the uniform rational filter bank), and the methods based on the laplacian pyramid image structure. There are also many different applications for image fusion; such as fusing the different template but the same location and same property images, fusing the different spatial resolution images, fusing the different-sensor images, fusing partial out-of-focused images, etc. Different applications have different key studying topics. For example, one application is to analyze the materials of the land cover from the multi-spectral information, the most important thing for such an application is the fusion method can not distort the components of the original spectral information. The application of the medical images is to provide the visible inspection by doctors; thus, we only concern whether all visible information is preserved in the fused images; we don’t care whether the spectral information is changed. From above fusion procedure, the fused images can provide more information for our following detection and decision. The ultimate goal of this research project is to detect targets from any possible sensor. The meaning of target detection is using the aerial-born visible images and using middle-distance passive infrared sensor to get the infrared images. At last, we combine these two kinds of images for land target detection. In the past years, we have completed several related works, such as the multi-spectral image segmentation, infrared image synthesis, wavelet-based texture segmentation, cloud removal, terrain visualization, etc. In the first-year project, we have completed: (i) image registration method, and (ii) IHS-based, PCA-based, and wavelet-selection-based fusion methods; thus we are confident to complete the execution of this-year research project. 研究期間：9901 ~ 9912 |
