000			03075cam a2200325 i 4500
001			966609831
003			OCoLC
005			20240220113015.0
008			170117t20182016nyua b 001 0 eng
010			_a2017001581
020			_a9789673498475 (paperback)
035			_a(OCoLC)966609831 _z(OCoLC)981989534 _z(OCoLC)1100468240 _z(OCoLC)1201929209
040			_aDLC _beng _erda _cDLC _dBTCTA _dBDX _dOCLCO _dOCLCF _dYDX _dYDX _dOCLCO _dIAK _dMUU _dMNX _dMOF _dCAI _dI8M _dOCLCQ _dIL4J6 _dOCLCO _dCDN _dMUU
042			_apcc
082	0	0	_a621.367 _223
100	1		_aGonzalez, Rafael C., _eauthor
245	1	0	_aDigital image processing / _cRafael C. Gonzalez, University of Tennessee, Richard E. Woods, Interapptics
250			_aFourth edition
264		1	_aNew York, NY : _bPearson, _c©2018.
300			_a1019 pages : _billustrations (some color) ; _c24 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references (pages 1143-1155) and index
505	0		_aIntroduction -- Digital image fundamentals -- Intensity transformations and spatial filtering -- Filtering in the frequency domain -- Image restoration and reconstruction -- Wavelet and other image transforms -- Color image processing -- Image compression and watermarking -- Morphological image processing -- Image segmentation I -- Image segmentation II active contours : snakes and level sets -- Feature extraction -- Image pattern classification
520			_a"For 40 years, Image Processing has been the foundational text for the study of digital image processing. The book is suited for students at the college senior and first-year graduate level with prior background in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming. As in all earlier editions, the focus of this edition of the book is on fundamentals. The 4th Edition, which celebrates the book's 40th anniversary, is based on an extensive survey of faculty, students, and independent readers in 150 institutions from 30 countries. Their feedback led to expanded or new coverage of topics such as deep learning and deep neural networks, including convolutional neural nets, the scale-invariant feature transform (SIFT), maximally-stable extremal regions (MSERs), graph cuts, k-means clustering and superpixels, active contours (snakes and level sets), and exact histogram matching. Major improvements were made in reorganizing the material on image transforms into a more cohesive presentation, and in the discussion of spatial kernels and spatial filtering. Major revisions and additions were made to examples and homework exercises throughout the book. For the first time, we added MATLAB projects at the end of every chapter, and compiled support packages for you and your teacher containing, solutions, image databases, and sample code."--Amazon.com
650		0	_aImage processing _xDigital techniques
700	1		_aWoods, Richard E. _q(Richard Eugene), _d1954- _eauthor
942			_2ddc _cBK _n0
999			_c485621 _d485621