Learning computer vision and image processing.
including some projects in the Digital Image Processing course.
- 01 - histogram-equalization-pro: some algorithms which based on the histogram equalization.
- 02 - retinex: implement and compare different retinex algorithms, like SSR, MSR, MSRCR etc.
- 03 - haze-night-image-enhancement: implement Dark Channel algorithm to enhance haze and night images.
- 04 - UM-AUM: implement and compare Unsharp Masking and Adaptive Unsharp Masking algorithms.
including some projects in the 3D Vision course.
- 01 - De-noising: Using ROF(Rudin-Osher-Fatemi) algorithm and Chambolle's method to solve the de-noising task.
- 02 - Panorama: Using SIFT, homography, Ransac algorithms to synthesis three images and get a panorama image.
- 03 - AR-system: A simple implement of AR system.
- 04 - 3D-Structure-recover: 3D structure recover based on two image views.
- 05 - Final-personal-project: Select a paper about Five-point algorithm and compare it with Seven-point and Eight-point algorithms.
including some projects from other courses or internet.
- image-alignmnet: This assignment from Coursera Deep Learning in Computer Vision course.
- face-alignment: Clearly practice for face alignment.
- edge-detection: Canny edge detection algorithm implement by Python3.
- histogram-equalization: learning histogram equalization.