課程大綱 Syllabus |
學生學習目標 Learning Objectives |
單元學習活動 Learning Activities |
學習成效評量 Evaluation |
備註 Notes |
序 No. | 單元主題 Unit topic |
內容綱要 Content summary |
1 | Introduction of image processing |
Why image processing is needed
Applications and problems with image processing |
The importance of image processing in modern time |
講授
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2 | Representation of color images |
Basic color theories
Color spaces |
How color information is perceived
How color signals is generated and represented
Color spaces |
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3 | Representation of color images |
Basic color theories
Color metric |
How color information is measured and used for digital processing
Color metric |
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4 | Representation of digital images |
Image signals represented in spatial domain
Sampling theory for image processing |
The form of image signals to be processed in the spatial domain |
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5 | Representation of digital images |
Image signals represented in frequency domains
Human visual systems (HVS)
Image display basics |
The form of image signals to be processed in the frequency domain
The characteristics of human visual perception |
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6 | Image enhancement |
Image processing using digital filtering techniques
Homomorphic filtering
Phase contrast filtering |
Image enhancement using digital filterings |
講授 實作
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平時考
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7 | Image enhancement |
Histrogram modification
Median filtering |
Image enhancement using statistical information |
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8 | Image enhancement |
Image enhancement based on a number of other spatial-domain algotithms |
Image enhancement based on spatial-domain algotithms |
講授 實作
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9 | Image transformation |
Why transforms are needed for 2D images
Unitary transform
Properties of unitary transforms
2-D Digital Fourier transform |
Basic concepts and fundamentals for two-dimensional digital image transformation |
講授 實作
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期中考
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10 | Image transformation |
2-D digital Fourier transform
2-D discrete cosine transform
2-D Haar transform
2-D Hadamart transform |
Well-known 2-D transforms for image processing |
講授 實作
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11 | Image transformation |
Karhunen-Loeve transform
Wavelet transform
Fractal transform |
The optimum transform for 2D images
Famous transforms for image analysis and data compression |
講授 實作
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12 | Image analysis |
Edge detection
Corner detection |
Basic techniques for image feature extraction |
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13 | Image analysis |
Hough transform |
Basic techniques for image feature extraction |
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14 | Image watermarking |
Basic concept of digital image watermarking
Spatial-domain methods for digital image watermarking
Frequency-domain methods for digital image watermarking |
Basic techniques for digital image watermarking |
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15 | Image compression |
Basic concept of data compression
Basic theories of source coding
Basic techniques of image coding |
Basic concept of data compression
Basic theories of source coding
Basic techniques of image coding |
講授 實作
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16 | Image compression |
Quantization
Predictive coding
Variable length coding |
Basic compression techniques in the spatial domain |
講授 實作
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17 | Image compression |
Vector quantization
DPCM
Transform coding |
Vector quantization
Coding techniques in the frequency domain |
講授 實作
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18 | Image compression |
Compression techniques used in the JPEG coding standard |
A case study on the JPEG coding standard |
講授 實作
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期末考
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