Description
TABLE OF CONTENT
1 . Introduction to Image Processing
Overview of Image Processing
Importance and Applications
2 . Basics of Python for Image Processing
Python Programming Fundamentals
Libraries for Image Processing (e.g., NumPy, OpenCV)
3 . Image Representation and Manipulation
Understanding Image Pixels
Image Types (RGB, Grayscale, Binary)
Basic Image Operations
4 . Image Filtering and Enhancement
Convolution and Filters
Blurring and Sharpening
Histogram Equalization
5 . Image Transformation and Geometric Operations
Image Rotation, Translation, and Scaling
Affine and Perspective Transformations
6 . Color Spaces and Channels
RGB, HSV, CMYK
Extracting and Manipulating Color Channels
7 . Feature Extraction and Object Detection
Edge Detection (Sobel, Canny)
Corner Detection (Harris Corner Detection)
Object Detection Techniques
8 . Image Segmentation
Thresholding
Region-based Segmentation
Watershed Algorithm
9. Image Compression
Introduction to Compression
Lossless and Lossy Compression
JPEG and PNG Compression
10 . Deep Learning for Image Processing
Introduction to Neural Networks
Convolutional Neural Networks (CNNs)
Transfer Learning for Image Classification
11 . Image Restoration
Noise Reduction Techniques
Image Denoising Algorithms
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