전체 글120 4.1 Filtering vs Convolution In this class, we will learn about Filtering vs Convolution. ● Filters We have learned Box, Gaussian, Sobel, Laplace filters. Let's compare Filtering and Convolution. There is a difference between filtering and convolution. Filter flipped vertically and horizontally. ● Derivative Theorem of Convolution ① Commutative - can move stuff around ② Associative - can regroup things ③ Distributes over ad.. 2020. 8. 5. 4.0 Image Gradients and Gradient Filtering In this class, we will learn about Image Gradients and Gradient Filtering. ● Image Edge We can view an image as a 2D function. How can we detect an edge? What kinds of filter should we use? ● Forward Difference We have learned the formula above in high school. The derivative of a function f at a point x is defined by the limit. The formula above is the approximation of the derivative when h is s.. 2020. 8. 4. 3.1 Image Pyramid In last class, we learned about Image Pyramid. ● Image Pyramid Application Image Pyramid can be used in many ways. Image compression, Multi-scale texture mapping, Image blending, Multi-focus composites, Noise removal, Hybrid images, Multi-scale detection, Multi-scale registraion....etc ● Constructing a Gaussian Pyramid When we construct the Gaussian Pyramid, the whole pyramid is only 4/3 the siz.. 2020. 8. 3. 3.0 Image Subsampling In this class, we will learn about Image Subsampling. Sometimes, an image is too big to fit on the screen. We should reduce the image to show the whole image in the screen. ● Naive image sub-sampling Naive image sub-sampling throws away even rows and columns. By doing so, we can reduce the image's size by half and repeat again and again. But what are the problems with this approach? As the image.. 2020. 8. 3. 이전 1 2 3 4 5 ··· 30 다음
