PDF: Digital Image Processing Using Matlab-muya-part2
本书是DIPUM的第二版,编者Rafael C.Gonzalez。 共压缩成三部分。 注意,需Part1-Part3 三部分都下载了才能解压缩。 (提醒:本书为扫描版,不算清楚,但是也来之不易) For Image and Computer Vision, Image Processing, and Computer Vision courses. This is the first text that provides a balanced treatment of image processing fundamentals and an introduction to software principles used in the practical application of image processing. A seamless integration of material from the leading text, Digital Image Processing by Gonzalez and Woods and the Image Processing Toolbox from Mathworks, Inc. This text works in the MATLAB computing environment; the Toolbox provides a stable, well-supported set of software tools capable of addressing a broad spectrum of applications in digital image processing. The major areas covered include intensity transformations, linear and nonlinear spatial filtering, filtering in the frequency domain, image restoration and registration, color image processing, wavelets, image data compression, morphological image processing, image segmentation, regions and boundary representation and description, and object recognition. From the Back Cover Digital Image Processing Using MATLAB is the first book that provides a balanced treatment of image processing fundamentals and the software principles used in their practical implementation. The book integrates material from the leading text, Digital Image Processing by Gonzalez and Woods, and the Image Processing Toolbox of the MathWorks. Inc., a recognized leader in scientific computing. The Image Processing Toolbox provides a stable, well-supported set of software tools for addressing a broad range of applications in digital image processing. A unique feature of this hook is its emphasis on showing how to enhance those tools by the development of new code. This is important in image processing, where there is a need for extensive experimental work in order to arrive at acceptable problem solutions. After an introduction to the fundamentals of MATLAB programming, the book addresses the mainstream areas of image processing. Areas covered include intensity transformations, linear and nonlinear spatial filtering, filtering in the frequency domain, image restoration and registration, color image processing, wavelets, image data compression, morphological image processing, image segmentation, regions and boundary representation and description, and object recognition.
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