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020 _a9780750359696
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024 7 _a10.1088/978-0-7503-5969-6
_2doi
035 _a(CaBNVSL)thg00084075
035 _a(OCoLC)1478800743
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aTA16374b.T553 2024eb
072 7 _aUYT
_2bicssc
072 7 _aCOM012050
_2bisacsh
100 1 _aThiruvikraman, P. K.,
_eauthor.
_997125
245 1 2 _aA course on digital image processing with MATLAB /
_cP.K. Thiruvikraman.
250 _aSecond edition.
264 1 _aBristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :
_bIOP Publishing,
_c[2024]
300 _a1 online resource (various pagings) :
_billustrations (some color).
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
490 1 _a[IOP release $release]
490 1 _aIOP ebooks. [2024 collection]
500 _a"Version: 20241101"--Title page verso.
504 _aIncludes bibliographical references.
505 _a1. Introduction -- 1.1. The scope and importance of digital image processing -- 1.2. Images -- 1.3. Digital images -- 1.4. Processes involved in image processing and recognition -- 1.5. Applications of image processing
505 8 _a2. Image enhancement in the spatial domain -- 2.1. Enhancement of contrast -- 2.2. Gray level transformations -- 2.3. Bit plane slicing -- 2.4. Histogram processing -- 2.5. Filtering in the spatial domain -- 2.6. Sharpening in the spatial domain
505 8 _a3. Filtering in the Fourier domain -- 3.1. From the Fourier series to the Fourier transform -- 3.2. Meaning of the Fourier transform -- 3.3. The impulse function -- 3.4. Fourier transform of a train of impulses -- 3.5. The convolution theorem -- 3.6. The discrete Fourier transform (DFT) -- 3.7. Additional properties of the DFT -- 3.8. Filtering in the Fourier domain -- 3.9. Low-pass filters -- 3.10. Other low-pass filters -- 3.11. High-pass filters -- 3.12. The FFT -- 3.13. Comparison of the FFT with convolution
505 8 _a4. Image compression -- 4.1. Basics of image compression -- 4.2. Basics of coding theory -- 4.3. Uniquely decodable codes (UDCs), instantaneously decodable codes (IDCs), and all that -- 4.4. Kraft's inequality -- 4.5. Efficiency of instantaneous codes -- 4.6. Information theory -- 4.7. Huffman coding : algorithm -- 4.8. Huffman coding : implementation -- 4.9. Nearly optimal codes -- 4.10. Reducing interpixel redundancy : run-length coding -- 4.11. LZW coding -- 4.12. Arithmetic coding -- 4.13. Transform coding
505 8 _a5. Image analysis and object recognition -- 5.1. Image analysis -- 5.2. Detection of points and lines -- 5.3. The Hough transform -- 5.4. Segmentation : edge detection -- 5.5. Thresholding -- 5.6. A global view of image analysis and pattern recognition -- 5.7. Representation of objects -- 5.8. Texture -- 5.9. Skeletonization or medial axis transformation (MAT) -- 5.10. Principal component analysis (PCA) -- 5.11. Pattern recognition
505 8 _a6. Image restoration -- 6.1. Analyzing motion blur -- 6.2. Inverse filtering -- 6.3. Noise -- 6.4. Removal of noise by morphological operations -- 6.5. Alternative method for extracting and labeling connected components -- 6.6. Image reconstruction from projections
505 8 _a7. Wavelets -- 7.1. Wavelets versus the Fourier transform -- 7.2. The Haar wavelet transform -- 7.3. An alternative view of wavelets
505 8 _a8. Color image processing -- 8.1. The RGB color model -- 8.2. The CMY and CMYK color models -- 8.3. The hue, saturation, and intensity (HSI) color model
505 8 _a9. Introduction to MATLABª -- 9.1. Introduction -- 9.2. Help with MATLABª -- 9.3. Variables -- 9.4. Mathematical operations -- 9.5. Loops and control statements -- 9.6. Built-in MATLABª functions -- 9.7. Some more useful MATLABª commands and programming practices -- 9.8. Functions
505 8 _a10. The image processing toolbox -- 10.1. Introduction -- 10.2. Reading from an image file and writing into an image file -- 10.3. Fourier domain processing -- 10.4. Calculation of entropy -- 10.5. Huffman code -- 10.6. Arithmetic code -- 10.7. Segmentation -- 10.8. Hough transform -- 10.9. Some common error messages in MATLAB -- 10.10. Using the MATLAB AI chat playground to generate MATLAB code -- 10.11. Exercises
505 8 _a11. Video processing -- 11.1. Introduction -- 11.2. Extracting frames from a video -- 11.3. Video compression -- 11.4. Detection and analysis of motion : optical flows -- 11.5. Exercises
505 8 _a12. Applications of machine learning -- 12.1. Linear discriminant analysis -- 12.2. Clustering using the k-means algorithm -- 12.3. K nearest neighbours -- 12.4. Artificial neural networks -- 12.5. Multilayer feedforward neural networks -- 12.6. Matrix formulation of ANNs -- 12.7. Back propagation for training neural networks
505 8 _a13. Error correcting codes and cryptography -- 13.1. Mutual information and channel capacity -- 13.2. Linear codes -- 13.3. Decoding linear codes -- 13.4. Cyclic codes -- 13.5. Galois fields -- 13.6. Cryptography -- 13.7. Encryption techniques -- 13.8. Public key cryptography -- 14. Solutions to selected exercises.
506 _aFull-text restricted to subscribers or individual document purchasers.
520 3 _aDigital imaging is now ubiquitous, from the smart phone in your pocket to state-of-the-art medical imaging and satellite imagery. Raw imaging data can be manipulated using computer algorithms to perform a range of functions from reducing noise to complex image analysis and pattern and object recognition. The result is that digital image processing has applications in almost all areas of science and engineering. Designed for a one semester course, the aim of this book is to concentrate on the principles and techniques of image processing. This second edition includes important updates to the first edition, as well as two entirely new chapters, making the book ideal for advanced students in physics and engineering.
521 _aProfessional and scholarly.
530 _aAlso available in print.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
545 _aP.K. Thiruvikraman is a professor of physics at the Birla Institute of Technology & Science with a research interest in Digital Image Processing, Pattern Recognition / Machine Vision and Coding Theory. The author has been teaching at BITS Pilani for the last 20 years. He has taught Digital Image Processing for more than a decade.
588 _aTitle from PDF title page (viewed on December 13, 2024).
630 _aMATLAB.
_995171
650 _aImage processing
_xDigital techniques.
_964228
650 7 _aImage processing.
_2bicssc
650 7 _aCOMPUTERS / Image Processing.
_2bisacsh
_997126
710 2 _aInstitute of Physics (Great Britain),
_epublisher.
_917702
776 8 _iPrint version:
_z9780750359672
_z9780750359702
830 0 _aIOP (Series).
_pRelease 24.
830 _aIOP ebooks.
_p2024 collection.
856 4 _uhttps://iopscience.iop.org/book/mono/978-0-7503-5969-6
942 _cE-Books
999 _c68522
_d68522