基于matlab的數(shù)字圖像處理仿真分析畢業(yè)論文-文庫吧資料
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【正文】 continuum: low, mid, and highever processes. Lowlevel processes involve primitive operation such as image preprocessing to reduce noise, contrast enhancement, and image sharpening. A lowlevel process is characterized by the fact that both its input and output are images. Midlevel processing on images involves tasks such as segmentation (partitioning an image into regions or objects), description of those objects to reduce them to a form suitable for puter processing, and classification (recognition) of individual object. Amidlevel process is characterized by the fact that its inputs generally are images, but its output is attributes extracted from those images (e. g., edges contours, and the identity of individual object). Finally, higherlevel processing involves “making sense” of an ensemble of recognized objects, as in image analysis, and, at the far end of the continuum, performing the cognitive function normally associated with vision. Based on the preceding ments, we see that a logical place of overlap between image processing and image analysis is the area of recognition of individual regions or objects in an image. Thus, what we call in this book digital image processing enpasses processes whose inputs and outputs are images and, in addition, enpasses processes that extract attributes from images, up to and including the recognition of individual objects. As a simple illustration to clarify these concepts, consider the area of automated analysis of text. The processes of acquiring an image of the area containing the text. Preprocessing that images, extracting (segmenting) the individual characters, describing the characters in a form suitable for puter processing, and recognizing those individual characters are in the scope of what we call digital image processing in this book. Making sense of the content of the page may be viewed as being in the domain of image analysis and even puter vision, depending on the level of plexity implied by the statement “making sense.” （二）中文翻譯數(shù)字圖像處理方法的研究 1 緒論 數(shù)字圖像處理方法的研究源于兩個主要應用領(lǐng)域:其一是為了便于人們分析而對圖像信息進行改進；其二是為了使機器自動理解而對圖像數(shù)據(jù)進行存儲、傳輸及顯示。 (4)to discuss briefly the principal approaches used in digital image processing。 (2)to give a historical perspective of the origins of this field。 ，(MATLAB版)[M].北京:電子工業(yè)出版社,[19] 陳懷琛. MATLAB及其在理工課程中的應用指南（第三版）[M].西安：西安電子科技大學出版社,文獻翻譯（1） 英文原文The research of digital image processing technique 1 Introduction Interest in digital image processing methods stems from two principal application areas: improvement of pictorial information for human interpretation。參考文獻[1] [M].[2] 高展宏，[M].北京：清華大學出版社[3] 李從利，、算法及實現(xiàn)[M].安徽：全國百佳圖書出版社 [4] 張強，王正林. 精通MATLAB圖像處理（第二版）[M].北京電子工業(yè)出版社，[5] 段一平,李浩攀. MATLAB在圖像處理中的應用[J]. 科技信息. 2009(10) [6] 尹鳳領(lǐng),霍丙全. 圖像處理技術(shù)的Matlab實現(xiàn)[J]. 科技信息. 2007(05) [7] 周偉. 基于MATLAB的數(shù)字圖像處理技術(shù)概述[J]. 信息與電腦(理論版). 2010(05)[8] 周廣芬,李鵬,[J]. 河北科技大學學報. 2005(04) [9] 劉中合,王瑞雪,王鋒德,馬長青,[J]. 計算機時代. 2005(09) [10] 包宋建,許艷英,陳帥華,湯勇. MATLAB語言在數(shù)字圖像處理中的應用[J]. 工業(yè)控制計算機. 2011(06) [11] 李昕,陳堅. 基于MATLAB的數(shù)字圖像處理[J]. 電腦知識與技術(shù). 2009(08) [12] 黃劍玲. 利用MATLAB進行數(shù)字圖像的分析和處理[J]. 計算機與現(xiàn)代化. 2000(06) [13] 鄧紅濤,趙慶展. 基于Matlab的圖像處理的研究[J]. (04) [14] 涂望明,魏友國,[J].(06)[15] 關(guān)雪梅. MATLAB處理數(shù)字圖像的方法研究[J]. (20)[16] 唐蘇湘. 圖像處理常用軟件的比較與應用[J]. 四川兵工學報. 2009(05) [17] 梁原. 基于MATLAB的數(shù)字圖像處理系統(tǒng)研究[D]. 長春: [18] 張長江,汪曉東，汪金山. 基于MATLAB的《數(shù)字圖像處理》綜合實驗設(shè)計[A]. 2008年中國高
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