Comprehensive Digital Image Processing Notes and Numericals
Edge Detection Using 1st Derivative
Original Image Function f(x)
First Derivative ∂f / ∂x
First Derivative Absolute Value |∂f / ∂x|
Local Extrema Indicate Edges
Local Maxima Indicate Edges
The first derivative provides both the location and strength of an edge.
2D Edge Detection
I(x, y): Edge
Basic Calculus: Partial derivatives of a 2D continuous function represent the amount of change along each dimension.
Gradient (∇)
Gradient (Partial Derivatives) represents the direction of most rapid chan
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Open Full Note in Study App →Why this study note is highly rated:
- Covers a wide range of important Digital Image Processing topics comprehensively, including edge detection, DCT, image restoration, and segmentation.
- Includes useful structural comparisons for edge operators (Sobel, Prewitt, Roberts) and thresholding rules (Standard vs. Hysteresis).