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.