Video lecture series on Digital Image Processing, Lecture: 31,
Color Fundamentals in Color Image Processing for Digital Image Processing ||RGB||CMYK||Chromaticity
Why do we use color in Image Processing?
What are different categories/areas/types of color image processing?
What is Full color image processing?
What is Pseudo color image processing?
Explain Color Fundamentals.
What is Radiance, Luminance and Brightness?
What is Hue, Saturation and Intensity?
How do we see any object?
How human eyes sense light?
What are Primary and Secondary colors?
What is the difference between primary colors of light and primary colors of pigments?
What are Tri-stimulus values?
What are Tri-chromatic coefficients?
Explain the Chromaticity diagram.
What are RGB and CMYK colors?
What is RGB Gamut of monitors?
What is Color gamut of printers?
Link to download ppts/lecture notes:
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Links of other lectures in the series:
1. What is Digital Image Processing?
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2. Human Visual System and Elements of Digital Image Processing
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3. Fundamental steps in Digital Image Processing
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4. Image Sensing and Acquisition
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5. Relationship between Pixels in Digital Image Processing: Neighborhood, Adjacency & Distance measures
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6. Image Sampling and Quantization
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7. Spatial and Intensity resolution in Digital Image Processing and its Implementation in MATLAB
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8. Basics of intensity transformations and spatial filtering and implementation in MATLAB
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9. Image negatives, Log and Power-Law transformations for DIP and implementation in MATLAB
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10. Piecewise linear transformation function: Contrast Stretching in DIP & implementation in MATLAB
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11. Piecewise linear transformation function: Intensity-level slicing in DIP and implementation in MATLAB
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12. Piecewise linear transformation function: Bit-plane slicing in DIP and implementation in MATLAB
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13. Histogram Equalization in DIP and its implementation in MATLAB
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14. Histogram Matching/Specification in Digital Image Processing with example and perform in MATLAB
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15. Fundamentals of Spatial filtering and Smoothing spatial filters in Digital Image Processing & MATLAB
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16. Order statistics/Non-linear (Median, Minimum and Maximum) spatial filters in DIP with example & Implementation in MATLAB
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17. Image Sharpening in Digital Image Processing||Sharpening Spatial filters with examples||HPF||MATLAB
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18. Introduction to Image Enhancement in the frequency domain and different steps for filtering in the frequency domain for DIP
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19. Image Smoothing in frequency domain filtering and its Implementation in MATLAB
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20. Image Sharpening (HPF) in frequency domain filtering and its Implementation in MATLAB
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21. Laplacian, Unsharp masking/High Boost filtering in the frequency domain filtering and its Implementation in MATLAB
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22. Homomorphic Filtering in Digital Image Processing and its Implementation in MATLAB
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23. Image Degradation and Restoration and Model of Image Degradation and Restoration process
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24. Noise Models with examples in Digital Image Processing/DIP
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25. Periodic Noise, Noise Estimation and Band Pass/Band Reject filters and its implementation in MATLAB
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26. Image Restoration in the Presence of Noise Only-Spatial Filtering with examples/calculations for DIP
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27. Estimating the Degradation function in Digital Image Processing |Observation |Experimentation |Modelling
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28. Inverse Filtering in Digital Image Processing and its implementation in MATLAB
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29. Wiener(Minimum Mean Square Error)Filter in Digital Image Processing and its implementation in MATLAB
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30. Constrained Least Squares Filtering(CLSF) in Digital Image Processing & its implementation in MATLAB
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