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 EE404: Digital Image Processing
                            Berkeley數字圖像處理視頻課程
(28課時  ¥48)
Instructor: Professor Avideh Zakhor

        Digital Image Processing是UC Berkeley電子工程專業(yè)高年級本科生課程。課程共28講,每講80分鐘左右,包括:.rm格式的課程視頻和與視頻課程內容配套使用的完整的課程講義。有了課程講義讓您的學習更有效,在潛移默化中提高專業(yè)知識和英語能力。
        加州大學伯克萊分校(UC Berkeley)作為世界一流大學,有著世界頂級的大師,所設課程也都是精品中的精品,緊跟最新科技的進展。本站推出的美國一流大學精品視頻課程套裝,讓您足不出戶就能一睹世界一流大學大師教學的風采;聆聽大師的聲音、拓展國際化的視野、與國際水平看齊、實現自我價值的提升。

 

 

Course Description:

        2-D sequences and systems, separable systems, projection slice thm, reconstruction from projections and partial Fourier information, Z transform, different equations, recursive computability, 2D DFT and FFT, 2D FIR filter design; human eye, perception, psychophysical vision properties, photometry and colorimetry, optics and image systems; image enhancement, image restoration, geometrical image modification, morphological image processing, halftoning, edge detection, image compression: scalar quantization, lossless coding, huffman coding, arithmetic coding dictionary techniques, waveform and transform coding DCT, KLT, Hadammard, multiresolution coding pyramid, subband coding, Fractal coding, vector quantization, motion estimation and compensation, standards: JPEG, MPEG, H.xxx, pre- and post-processing, scalable image and video coding, image and video communication over noisy channels.
 

Outline of Topics::

1. Image reconstruction from partial information
2. Two-dimensional (2-D) Fourier transform and z-transform;
3. 2-D DFT and FFT, FIR and IIR filter design and implementation.
4. Basics of Image Processing techniques and perception;
5. Image and video enhancement
6. Image and video restoration
7. Reconstruction from multiple images
8. Image and video analysis: Image Representation and models; image and video classfication and segmentation; edge and boundary detection in images
9. Image compression and coding
10. Video compression
11. Image and Video Communication, storage and retreival
12. Image and video rendering and assessment
13. Image and video Acquisition
14. Applications of image processing: Synthetic Aperture Radar, computed tomography, cardiac image processing, finger print classfication, human face recognition.
 

Textbooks:

1. Bovik, Handbook of Image and Video Processing, Academic Press 2000, (recommended)
2. N. Netravali and Barry G. Haskell, Digital Pictures, Plenum Press, 1988. (recommended)
3. W. K. Pratt, Digital Image Processing, John Wiley and Sons, 1992. (recommended)
4. M. Tekalp, Digital Video Processing, Prentice Hall, 1995. (recommended)
 

Course Schedule

Lecture #1: introduction
Lecture #2: Systems, Jan. 20, 2006
Lecture #3: Tomography, Jan. 25, 2006
Lecture #4: Reconstruction of 2-D Signals from Partial Fourier Information, Jan. 27, 2006
Lecture #5: Detour into Numerical Analysis, Feb. 1, 2006
Lecture #6: Reconfiguration of M-D Signals From Zero Crossings, Feb. 3, 2006
Lecture #7: Filters (LSI System), Feb. 8, 2006
Lecture #8: How to Choose B.C. for 2D D.L.C.C.D.E., Feb. 10, 2006
Lecture #9: Computing DFT, Feb. 15, 2006
Lecture #10: Filter Specs, Feb. 17, 2006
Lecture #11: Example of 2D FIR, Feb. 22, 2006
Lecture #12: 2D Filter Design Using Transformation, Feb. 24, 2006
Lecture #13: Human Visual System, Mar. 1, 2006
Lecture #14: Image Enhancement, Mar. 3, 2006
Lecture #15: Mathematical Aspects/Derivation of Histogram Equalization, Mar. 8, 2006
Lecture #16: Local Enhancements Using Local Histogram Analysis, Mar. 10, 2006
Lecture #17: Image Enhancement, Mar. 15, 2006
Lecture #18: Image Restoration, Mar. 17, 2006
Lecture #19: Image Restoration continued, Mar. 22, 2006
Lecture #20: Restoration, Mar. 24, 2006
Spring Break, Mar. 27-31, 2006
Lecture #21: Adaptive Weiner Filtering, Apr. 5, 2006
Lecture #22: Image Restoration, Apr. 7, 2006
Lecture #23: Image Restoration cont., Apr. 12, 2006
Lecture #24: Image Coding, Apr. 14, 2006
Lecture #25: Image Compression, Apr. 19, 2006
Lecture #26: DPCM, Apr. 21, 2006
Lecture #27: Discrete Cosine Transform and it's Use in Image Compression, Apr. 26, 2006
Lecture #28: Lossy Image Compression, Apr. 28, 2006
Lecture #29: Multiresolution, May 3, 2006
 

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