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Titlebook: Digital Image Processing; An Algorithmic Intro Wilhelm Burger,Mark J. Burge Textbook 20162nd edition Springer-Verlag London Ltd., part of S

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發(fā)表于 2025-3-21 19:56:33 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Digital Image Processing
副標(biāo)題An Algorithmic Intro
編輯Wilhelm Burger,Mark J. Burge
視頻videohttp://file.papertrans.cn/280/279440/279440.mp4
概述Updated and expanded new edition.Presents an accessible introduction to the methods of digital image processing.Describes the most important procedures, with formal and mathematical aspects discussed
叢書名稱Texts in Computer Science
圖書封面Titlebook: Digital Image Processing; An Algorithmic Intro Wilhelm Burger,Mark J. Burge Textbook 20162nd edition Springer-Verlag London Ltd., part of S
描述This revised and expanded new edition of an internationally successful classic presents an accessible introduction to the key methods in digital image processing for both practitioners and teachers. Emphasis is placed on practical application, presenting precise algorithmic descriptions in an unusually high level of detail, while highlighting direct connections between the mathematical foundations and concrete implementation.?.The text is supported by practical examples and carefully constructed chapter-ending exercises drawn from the authors‘ years of teaching experience, including easily adaptable Java code and completely worked out examples. Source code, test images and additional instructor materials are also provided at an associated website. .Digital Image Processing.?is the definitive textbook for students, researchers, and professionals in search of critical analysis and modern implementations of the most important algorithms in the field, andis also eminently suitable for self-study..
出版日期Textbook 20162nd edition
關(guān)鍵詞Digital Image Processing; Discrete Fourier Transform; GSM - Postponed Project; Image Processing; Image P
版次2
doihttps://doi.org/10.1007/978-1-4471-6684-9
isbn_ebook978-1-4471-6684-9Series ISSN 1868-0941 Series E-ISSN 1868-095X
issn_series 1868-0941
copyrightSpringer-Verlag London Ltd., part of Springer Nature 2016
The information of publication is updating

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ImageJ,ssing tools or, out of necessity, developed their own software packages. Usually such home-brew environments started out with small software components for loading and storing images from and to disk files. This was not always easy because often one had to deal with poorly documented or even proprie
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Histograms and Image Statistics,lems in an image, for example, it is simple to conclude if an image is properly exposed by visual inspection of its histogram. In fact, histograms are so useful that modern digital cameras often provide a real-time histogram overlay on the viewfinder (Fig. 3.1) to help prevent taking poorly exposed
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Filters, . position. The capabilities of point operations are limited, however. For example, they cannot accomplish the task of . or . an image (Fig. 5.1). This is what filters can do. They are similar to point operations in the sense that they also produce a 1:1 mapping of the image coordinates, that is, t
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Finding Simple Curves: The Hough Transform,entation at every position in the image. In the following sections, we explain how to decide (e.g., by using a threshold operation on the edge strength) if a curve is actually present at a given image location. The result of this process is generally represented as a binary .. Edge maps are consider
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Morphological Filters,1 illustrates once more how corners are rounded off, holes of a certain size are filled, and small structures, such as single dots or thin lines, are removed. The median filter thus responds selectively to the local shape of image structures, a property that might be useful for other purposes if it
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Automatic Thresholding, applications today because of their simplicity and efficiency. To obtain a binary image, the first and perhaps most critical step is to convert the initial grayscale (or color) image to a binary image, in most cases by performing some form of thresholding operation, as described in Chapter 4, Sec.
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