Sharpening & Edge Detection: Sobel Gx, Gy and Gradient Magnitude
This lesson is part of the course
In this lesson
You sharpen one pixel with a sharpening kernel, then run the Sobel kernels over an image with a bright block to find vertical and horizontal edges and combine them into the gradient magnitude.
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Lessons in this course
- Pixels as Numbers: RGB to Greyscale with Weighted Luminance Locked
- Brightness, Contrast & the Histogram (FREQUENCY, with a Chart) Locked
- Thresholding & Binary Masks: Separating an Object from the Background Locked
- 3×3 Convolution with SUMPRODUCT: a Gaussian Blur Locked
- Sharpening & Edge Detection: Sobel Gx, Gy and Gradient Magnitude Locked
- Padding & Stride: the Output-Size Formula and a Stride-2 Convolution Locked
- Max & Average Pooling: Shrinking Feature Maps Locked
- A Tiny CNN by Hand: Conv → ReLU → Pool → Score Locked