Defilter
Repository for Zero-order Reverse Filtering
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Intro To Computer Vision With Python Opencv | 43 | 6 years ago | Jupyter Notebook | |||||||
| An Introduction to Computer Vision using OpenCV with Python Bindings | ||||||||||
| Defilter | 29 | 6 years ago | 1 | mit | ||||||
| Repository for Zero-order Reverse Filtering | ||||||||||
| Opencvrealtimeedgedetection Ios | 19 | 10 years ago | 1 | Objective-C++ | ||||||
| Detecting edges using canny filtering in real-time to render a polygon on the video feed where the edges occur. Basically - we're outlining an item like a sheet of paper or something. | ||||||||||
| Noise Adaptive Switching Non Local Means | 16 | 8 years ago | 1 | Matlab | ||||||
| Aiming at the removal of salt-and-pepper noise, a noise adaptive switching non-local means denoising algorithm (NASNLM) is proposed in this program. For noise detection, the pixels of image are divided into the noise and the non-noise points. For filtering, four different filtering techniques are adopted: switching filtering, noise adaptive median filtering, edge-perserving filtering and non-local means filtering. Switching filtering can keep the gray-value of non-noise points unchanged. Noise adaptive median filtering can suppress the high-density salt-and-pepper noise. Edge-preserving filtering can preserve more image edges and details. Non-local means filtering can further improve the ability of noise suppression and detail maintenance. Experiments demonstrate that for removal of the high-density salt-and-pepper noise by NASNLM algorithm, a better denoising effect is obtained than other methods. | ||||||||||
| Dag.js | 12 |  | 2 | 4 | 6 years ago | 5 | June 12, 2018 | mit | JavaScript | |
| Simple DAG (Directed Acyclic Graph) with edge tagging | ||||||||||
| Carnd Lanelines P1 | 9 | 7 years ago | Python | |||||||
| Finding Lane Lines on the Road | ||||||||||
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