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Lecture Digital image processing: Introduction - Nguyễn Công Phương
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Lecture Digital image processing include the content: Introduction to Image processing and matlab; image acquisition, types, and file I/O; image arithmetic; spatial and frequency domain filter design; mage restoration and blind deconvolution;...
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Nội dung Text: Lecture Digital image processing: Introduction - Nguyễn Công Phương
- Nguyễn Công Phương
DIGITAL IMAGE PROCESSING
Introduction
- Contents
I. Introduction to Image Processing & Matlab
II. Image Acquisition, Types, & File I/O
III. Image Arithmetic
IV. Affine & Logical Operations, Distortions, & Noise in Images
V. Image Transform
VI. Spatial & Frequency Domain Filter Design
VII. Image Restoration & Blind Deconvolution
VIII. Image Compression
IX. Edge Detection
X. Binary Image Processing
XI. Image Encryption & Watermarking
XII. Image Classification & Segmentation
XIII. Image – Based Object Tracking
XIV. Face Recognition
XV. Soft Computing in Image Processing
sites.google.com/site/ncpdhbkhn 2
- References
[1] A. Das. Guide to Signals and Patterns in Image
Processing: Foundation, Methods and Application.
Springer, 2015.
[2] W. K. Pratt. Introduction to Digital Image
Processing. CRC Press, 2014.
[3] U. Qidwai, C. H. Chen. Digital Image
Processing: An Algorithmic Approach with
MATLAB®. CRC Press, 2009.
[4] L. P. Yaroslavsky. Theoretical Foundations of
Digital Imaging using MATLAB®. CRC Press, 2013.
[5] sites.google.com/site/ncpdhbkhn
sites.google.com/site/ncpdhbkhn 3
- Introduction
1. What is an Image?
2. Image Properties
3. Why Matlab?
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- What is an Image? (1)
• A digital image is a 2D y
signal.
• An image is a function
(e.g., brightness) of two
real variable a(x,y):
– a: amplitude, real number
or integer,
– (x,y): real coordinate
position.
• Pixel: picture element. 0 x
• Region of interest (ROI).
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- What is an Image? (2)
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- Image Properties (1)
• Signal – to – Noise Ratio (SNR):
signal _ power
SNR
noise _ power
• Image bit resolution (or image resolution): the
number of grayscale level or the number of
pixels present in the image.
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- Image Properties (2)
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- Image Properties (3)
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- Why Matlab?
• Images can be treated as matrices.
• Matlab is optimized for matrix operations.
• So …
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