000 | 03992nam a22005175i 4500 | ||
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001 | 978-3-031-02238-8 | ||
003 | DE-He213 | ||
005 | 20240730165009.0 | ||
007 | cr nn 008mamaa | ||
008 | 220601s2006 sz | s |||| 0|eng d | ||
020 |
_a9783031022388 _9978-3-031-02238-8 |
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024 | 7 |
_a10.1007/978-3-031-02238-8 _2doi |
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_a620 _223 |
100 | 1 |
_aWang, Zhou. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _986998 |
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245 | 1 | 0 |
_aModern Image Quality Assessment _h[electronic resource] / _cby Zhou Wang, Alan C. Bovik. |
250 | _a1st ed. 2006. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2006. |
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300 |
_aX, 146 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSynthesis Lectures on Image, Video, and Multimedia Processing, _x1559-8144 |
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505 | 0 | _aIntroduction -- Bottom-Up Approaches for Full-Reference Image Quality Assessment -- Top-Down Approaches for Full-Reference Image Quality Assessment -- No-Reference Image Quality Assessment -- Reduced-Reference Image Quality Assessment -- Conclusion. | |
520 | _aThis Lecture book is about objective image quality assessment-where the aim is to provide computational models that can automatically predict perceptual image quality. The early years of the 21st century have witnessed a tremendous growth in the use of digital images as a means for representing and communicating information. A considerable percentage of this literature is devoted to methods for improving the appearance of images, or for maintaining the appearance of images that are processed. Nevertheless, the quality of digital images, processed or otherwise, is rarely perfect. Images are subject to distortions during acquisition, compression, transmission, processing, and reproduction. To maintain, control, and enhance the quality of images, it is important for image acquisition, management, communication, and processing systems to be able to identify and quantify image quality degradations. The goals of this book are as follows; a) to introduce the fundamentals of image quality assessment, and to explain the relevant engineering problems, b) to give a broad treatment of the current state-of-the-art in image quality assessment, by describing leading algorithms that address these engineering problems, and c) to provide new directions for future research, by introducing recent models and paradigms that significantly differ from those used in the past. The book is written to be accessible to university students curious about the state-of-the-art of image quality assessment, expert industrial R&D engineers seeking to implement image/video quality assessment systems for specific applications, and academic theorists interested in developing new algorithms for image quality assessment or using existing algorithms to design or optimize other image processing applications. | ||
650 | 0 |
_aEngineering. _99405 |
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650 | 0 |
_aElectrical engineering. _986999 |
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650 | 0 |
_aSignal processing. _94052 |
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650 | 1 | 4 |
_aTechnology and Engineering. _987001 |
650 | 2 | 4 |
_aElectrical and Electronic Engineering. _987002 |
650 | 2 | 4 |
_aSignal, Speech and Image Processing. _931566 |
700 | 1 |
_aBovik, Alan C. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987003 |
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710 | 2 |
_aSpringerLink (Online service) _987005 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031011108 |
776 | 0 | 8 |
_iPrinted edition: _z9783031033667 |
830 | 0 |
_aSynthesis Lectures on Image, Video, and Multimedia Processing, _x1559-8144 _987007 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-02238-8 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
999 |
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