Chapter 4 Multiframe Super-resolution Image Reconstruction 1 - - PDF document

chapter 4 multiframe super resolution image reconstruction
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Chapter 4 Multiframe Super-resolution Image Reconstruction 1 - - PDF document

Chapter 4 Multiframe Super-resolution Image Reconstruction 1 Multi-frame SRIR (Video Enhancement) Low resolution video Our method LR image Source: https://users.soe.ucsc.edu/~milanfar/software/sr-datasets.html 2 1 Multi-frame SRIR


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Multiframe Super-resolution Image Reconstruction Chapter 4

LR image

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Multi-frame SRIR (Video Enhancement)

Low resolution video Our method

Source: https://users.soe.ucsc.edu/~milanfar/software/sr-datasets.html

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Input Video High-definition Video

Multi-frame SRIR (Video Enhancement)

  • 1. High-resolution Image Reconstruction
  • 2. Video Still Enhancement Models
  • Classical
  • Tight-frame
  • Low-rank
  • 3. Experiments
  • 1. High-resolution Image Reconstruction
  • 2. Video Still Enhancement Models
  • Classical
  • Tight-frame
  • Low-rank
  • 3. Experiments

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Outline

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Not one, but many lens— compound eyes

Super-resolution Image Reconstruction (SRIR)

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Super-resolution Image Reconstruction (SRIR)

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low-resolution pixel a b c d given intensity = (a+b+c+d)/4 high-resolution pixel LR 1 d LR 2 LR 3 LR 4 d

Modeling of SRIR

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Modeling of SRIR

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Modeling of SRIR

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Modeling of SRIR

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Outline

  • 1. High-resolution Image Reconstruction
  • 2. Video Still Enhancement Models
  • Classical
  • Tight-frame
  • Low-rank
  • 3. Experiments

Bilinear interpolation from 1 frame Tight-frame method using 21 frames

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A 352-by-288 video from a video recorder

[C., Shen, & Xia, ACHA 07]

Video Still Enhancement

30 frames/second frames are not aligned at exactly half-pixel length

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Reference frame t

displacement

Aligning the Frames

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High- resolution pixels Ideal low- resolution pixel position Displaced low- resolution pixel

Sub-pixel Displacement

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Modeling of Video Still Enhancement

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Modeling of SRIR

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Classical Approach [Tsai & Huang, 84]

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Outline

  • 1. High-resolution Image Reconstruction
  • 2. Video Still Enhancement Models
  • Classical
  • Tight-frame
  • Low-rank
  • 3. Experiments
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Low- resolution pixel High- resolution pixels

4 1 2 1 4 1 2 1 1 2 1 4 1 2 1 4 1

Tightframe Approach [C2 + S2, SISC (2003)]

Averaging process = a lowpass filter with refinement mask

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Piecewise Linear Tight Frame

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From LR Images to HR Image

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Key Observation

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Tightframe SRIR

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Outline

  • 1. High-resolution Image Reconstruction
  • 2. Video Still Enhancement Models
  • Classical
  • Tight-frame
  • Low-rank
  • 3. Experiments
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Low-rank Approach [ArXiv: 170406196]

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Motion Matrices in 1D

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Decomposition of the Motion Matrices

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Creating Low Rank Structure

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Variational Formulation

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Motion Matrices in 2D

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Creating Low Rank Structure

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Low-rank Super-resolution Model

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Nuclear Norm [Candes, Recht, 09; Recht, Fazel, Parrilo, 10]

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Motion Estimation

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Local Motion Estimation [C. Gilliam and T. Blu, 2015]

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Global Motion Estimation

[C., Shen and Xia, ACHA, 2007]

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Outline

  • 1. High-resolution Image Reconstruction
  • 2. Video Still Enhancement Models
  • Classical
  • Tight-frame
  • Low-rank
  • 3. Experiments

21 frames with tightframe

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Bookshelf Video Upsampled by 2

Single frame with bilinear interpolation 21 frames with nuclear norm 21 frames with TV regularization

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20 tightframe (2007)

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Disk Video Upsampled by 2

MAP (2015) nuclear sparse direct’l (‘10) LR video reference frame

Source: https://users.soe.ucsc.edu/~milanfar/software/sr-datasets.html

tightframe

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Text Video Upsampled by 2

MAP nuclear sparse directional LR video reference frame

Source: https://users.soe.ucsc.edu/~milanfar/software/sr-datasets.html

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21 tightframe

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Alpaca Video Upsampled by 2

MAP nuclear sparse directional LR video reference frame

Source: https://users.soe.ucsc.edu/~milanfar/software/sr-datasets.html

tightframe

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Alpaca Video Upsampled by 4

MAP nuclear sparse directional LR video reference frame

Source: https://users.soe.ucsc.edu/~milanfar/software/sr-datasets.html

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22 reference image

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Alpaca Image Upsampled by 4

nuclear tightframe

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EIA Video Upsampled by 4

MAP nuclear sparse directional LR video

Source: https://users.soe.ucsc.edu/~milanfar/software/sr-datasets.html

reference frame

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23 reference image

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EIA Image Upsampled by 4

nuclear sparse directional

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EIA Image Upsampled by 4

nuclear L1-robust, Farsiu et al. (2004) 10 x 10 (.jpg)

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24 tightframe

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Book-shelf Upsampled by 2

MAP nuclear sparse directional LR video reference frame tightframe

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Bookshelf Video Upsampled by 2

MAP nuclear sparse directional reference frame LR video

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25 true image tightframe

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Boat Video Upsampled by 2

MAP nuclear sparse directional LR video 25.76dB 20.88dB 26.94dB 18.66dB

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interpolate/inpaint interpolate/inpaint

Single Frame Upsampling

interpolate/inpaint

t t

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Input Video Qian et al. Siggraph 09: Upsampled by bicubic Level 6 Tightframe

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Qian et al. Siggraph 09 Upsampled by bicubic Level 6 Tightframe

No thresholding = completely parameter free

Input Video

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Concluding Remarks

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  • R. Zhao and R. Chan, arXiv:1704.06196