The document discusses a project to develop a video super-resolution system with a user interface. The goals are to allow users to zoom in on video frames with high resolution results. Current status includes successfully retrieving image streams from video and developing a graphic user interface with a video player that supports zooming in and out. Additional materials provide details on super-resolution algorithms, problems implementing iterative back projection, using bicubic interpolation as an initial upsampling method, and retrieving video frames using OpenCV.

1. Super-resolution on Video
with User Interface
薛健鑫, 蔡昆修, 何星翰
1

2. Super-resolution on Video
Our goal : User can zoom-in the video with high resolution
result when watching video.
2

3. Project Goals (Original)
Retrieving image stream
From raw image sequence
From DirectX
Super-resolution processing
Algorithm survey
GPU speedup investigation
Evaluation method
Graphic User Interface
Video player
Zoom in/out
3

4. Current Status
✔ Retrieving image stream
✔ From raw image sequence
✔ From OpenCV
Super-resolution processing
✔ Algorithm survey
GPU speedup investigation
Evaluation method
✔ Graphic User Interface
✔ Video player
✔ Zoom in/out
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5. Result Demo
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6. THE END
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7. Additional Material
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8. About SR algorithm
Reference: Practical Super-Resolution from Dynamic Video Sequences
Input: A target LR image and a sequence of neighbor LR image
Step 1. get initial HR image f0
Step 2. use forward projection to simulate those LR image.
Step 3. use the difference between ground truth LR and simulate
LR to do backward projection and make guess HR image f1
Step 4. After n iteration we get a HR image fn which can
simulate LR images which are very closed to ground truth.
Wei-Chao Chen
8
(weichao.chen@gmail.com)

9. Some Problems about IBP
We know the flow of algorithm, but some detail problems exist
1. How to get good f0 ?
2. The optical flow relation between LR neighbors and target
HR image.
3. The ‘Quality Pair’ examination algorithm in the paper ,
which is not clear in the paper.
4. BP algorithm with EWA filtering
Those questions are now bothering us and we need further
studies to solve them.
Wei-Chao Chen
9
(weichao.chen@gmail.com)

10. The initial estimation of HR
We regard the IBP as a further refinement , base on a good
initial upscaling result. It is also important to have a very
good f0 estimation in the IBP algorithm.
Bicubic resizing has very good result in upscaling and easy
to implement, so it is our first choice.
Wei-Chao Chen
10
(weichao.chen@gmail.com)

11. Retrieving image stream from video
Extract video frames by OpenCV
Load frame sequence in OpenGL as textures
Display video using texture animation technique
Wei-Chao Chen
11
(weichao.chen@gmail.com)