000 | 03640nam a22005775i 4500 | ||
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001 | 978-3-662-56497-4 | ||
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_a9783662564974 _9978-3-662-56497-4 |
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_a10.1007/978-3-662-56497-4 _2doi |
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_aDing, Yong. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _953362 |
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245 | 1 | 0 |
_aVisual Quality Assessment for Natural and Medical Image _h[electronic resource] / _cby Yong Ding. |
250 | _a1st ed. 2018. | ||
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2018. |
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300 |
_aX, 272 p. 102 illus. _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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_atext file _bPDF _2rda |
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505 | 0 | _aIntroduction -- Subjective Image Quality Assessment -- Human Visual System and Vision Modeling -- General Framework of Image Quality Assessment -- Image Quality Assessment Based on Human Visual System Properties -- Image Quality Assessment Based on Natural Scene Statistics -- Stereoscopic Image Quality Assessment -- Medical Image Quality Assessment -- Challenge Issues and Future Work. | |
520 | _aImage quality assessment (IQA) is an essential technique in the design of modern, large-scale image and video processing systems. This book introduces and discusses in detail topics related to IQA, including the basic principles of subjective and objective experiments, biological evidence for image quality perception, and recent research developments. In line with recent trends in imaging techniques and to explain the application-specific utilization, it particularly focuses on IQA for stereoscopic (3D) images and medical images, rather than on planar (2D) natural images. In addition, a wealth of vivid, specific figures and formulas help readers deepen their understanding of fundamental and new applications for image quality assessment technology. This book is suitable for researchers, clinicians and engineers as well as students working in related disciplines, including imaging, displaying, image processing, and storage and transmission. By reviewing and presenting the latest advances, and new trends and challenges in the field, it benefits researchers and industrial R&D engineers seeking to implement image quality assessment systems for specific applications or design/optimize image/video processing algorithms. | ||
650 | 0 |
_aSignal processing. _94052 |
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650 | 0 |
_aComputer vision. _953363 |
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650 | 0 |
_aComputer networks . _931572 |
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650 | 0 |
_aEngineering mathematics. _93254 |
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650 | 0 |
_aEngineering—Data processing. _931556 |
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650 | 1 | 4 |
_aSignal, Speech and Image Processing . _931566 |
650 | 2 | 4 |
_aComputer Vision. _953364 |
650 | 2 | 4 |
_aComputer Communication Networks. _953365 |
650 | 2 | 4 |
_aMathematical and Computational Engineering Applications. _931559 |
710 | 2 |
_aSpringerLink (Online service) _953366 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783662564950 |
776 | 0 | 8 |
_iPrinted edition: _z9783662564967 |
776 | 0 | 8 |
_iPrinted edition: _z9783662585832 |
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-662-56497-4 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
_c79135 _d79135 |