a super resolution algorithm for surveillance images

Post on 20-May-2015

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A paper presentation on super resolution algorithm using weighted Markov random fields

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High resolution

image

Low resolution image

Reconstructed with HWRF

Reconstructed with HWMRF

High resolution

image

Reconstructed with HWRF

Reconstructed with HWMRF

High Resolution Image

Warped

Blurred

Down-sampled

Low Resolution

Images

π‘€π‘˜ 𝐡 𝐷

𝐸 πœƒ = π‘¦π‘˜ βˆ’ π‘¦π‘˜(𝑙,πœƒ) 2

β€’ 𝑧 = π‘Žπ‘Ÿπ‘”π‘šπ‘Žπ‘₯ 𝑝 𝑦 𝑧 𝑝(𝑧)

𝑝(𝑦)

𝑧 = π‘Žπ‘Ÿπ‘”π‘šπ‘–π‘›[ β€–π‘¦π‘˜ βˆ’ π΄π‘˜π‘§β€–

π‘˜

2+ λ𝛀(𝑧)]

𝛀 z = 𝑉𝑐 𝑧 = π‘€π‘šπœŒ(𝑑𝑖,π‘—π‘šπ‘§)4

π‘š=1𝐿2𝑁2βˆ’1𝑗=0

𝐿1𝑁1βˆ’1𝑖=0π‘βˆˆπΆ

β€’ 𝑑𝑖,𝑗1 π‘₯ = π‘₯𝑖,𝑗+1 βˆ’ 2π‘₯𝑖,𝑗 + π‘₯𝑖,π‘—βˆ’1

β€’ 𝑑𝑖,𝑗2 π‘₯ =

2

2(π‘₯π‘–βˆ’1,π‘—βˆ’1 βˆ’ 2π‘₯𝑖,𝑗 + π‘₯𝑖+1,𝑗+1)

β€’ 𝑑𝑖,𝑗3 π‘₯ = π‘₯𝑖+1,𝑗 βˆ’ 2π‘₯𝑖,𝑗 + π‘₯π‘–βˆ’1,𝑗

β€’ 𝑑𝑖,𝑗4 π‘₯ =

2

2(π‘₯π‘–βˆ’1,𝑗+1 βˆ’ 2π‘₯𝑖,𝑗 + π‘₯𝑖+1,π‘—βˆ’1)

β€’ π‘Ÿ 𝑧 𝑛 = π΄π‘˜π‘‡ π΄π‘˜π‘§

𝑛 βˆ’ π‘¦π‘˜ +π‘˜ βˆ‡π›€ 𝑧 𝑛

β€’ π΄π‘˜π‘‡ π΄π‘˜π‘§

𝑛 βˆ’ π‘¦π‘˜ = π‘€π‘˜π‘‡π΅π‘‡π·π‘‡(π·π΅π‘€π‘˜π‘§

𝑛 βˆ’ π‘¦π‘˜)

High resolution image

Low resolution image

Reconstruction with HMRF

Reconstruction with HWMRF

High resolution image

Low resolution image

Reconstruction with HMRF

Reconstruction with HWMRF

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Surveillance image

Reconstruction using HMRF

Reconstruction using HWMRF

Surveillance image

Reconstruction using HMRF

Reconstruction using HWMRF

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