Image Processing 10. Convolution Kernel
1 min read June 29, 2025 #image processing #javascript
image processing (Series)
Image Processing 1. Introduction
Image Processing 2. Simple transformation
Image Processing 3. Negate filter, channel extraction and inversion
Image Processing 4. Desaturation
Image Processing 5. Color Models
Image Processing 6. Brightness, saturation, contrast, gamma correction
Image Processing 7. Histogram
Image Processing 8. Image scaling
Image Processing 9. Blur
Image Processing 10. Convolution Kernel
Image Processing 10. Convolution Kernel
Image Processing 1. Introduction
Image Processing 2. Simple transformation
Image Processing 3. Negate filter, channel extraction and inversion
Image Processing 4. Desaturation
Image Processing 5. Color Models
Image Processing 6. Brightness, saturation, contrast, gamma correction
Image Processing 7. Histogram
Image Processing 8. Image scaling
Image Processing 9. Blur
Image Processing 10. Convolution Kernel
Image Processing 10. Convolution Kernel
With convolution kernel it's possible to implement numerous interesting effects, such as motion blur, sharpening, edge detecting, emboss, etc. These effects we going to explore in this article.
If we modify the previous blur effect example with a radius 1 (i.e., examining 3×3 pixels) so that each color component from the 9 sampled pixels is multiplied by corresponding coefficients, summed, and then divided by some value – we get convolution.