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




             1
Super-resolution on Video
Our goal : User can zoom-in the video with high resolution
result when watching video.




                            2
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
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

                                 4
Result Demo




     5
THE END

   6
Additional Material

         7
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)
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)
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)
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)

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Gpgpu presentation 2

  • 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 4
  • 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)