# Picture Fusion for Context Enhancement and Video Surrealism

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. . Dim Bldgs. Reflections on bldgs. Obscure shapes. .

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﻿Picture Fusion for Context Enhancement and Video Surrealism Ramesh Raskar Mitsubishi Electric Research Labs, (MERL) Adrian Ilie UNC Chapel Hill Jingyi Yu MIT

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Dark Bldgs Reflections on bldgs Unknown shapes

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'Sufficiently bright' Bldgs Reflections in bldgs windows Tree, Street shapes

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Night Image Background is caught from day-time scene utilizing the same settled camera Context Enhanced Image Day Image

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Mask is consequently figured from scene differentiate

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But, Simple Pixel Blending Creates Ugly Artifacts

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Pixel Blending

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Pixel Blending Our Method : Integration of mixed Gradients

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Outline Context Enhancement Gradient-based Fusion Video Enhancement Surrealism

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Gradient field Nighttime picture x Y I 1 G 1 G 1 Mixed inclination field x Y G Importance picture W I 2 x Y G 2 G 2 Final outcome Daytime picture Gradient field

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Reconstruction from Gradient Field Problem: limit blunder | Ñ I' – G| Estimate I' so that G = Ñ I' Poisson condition Ñ 2 I' = div G Full multigrid solver G X I' G Y

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Why Gradient-based Approach Comparison of force qualities are vital Maintain angles to catch nearby varieties Directly understand for craved slopes Maintain unobtrusive points of interest Mix divergent pictures No requirement for exact division

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Comparison Average Subtle points of interest are lost Pixel-wise mixing Sharp moves

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Issues Boundary conditions Color movements

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Boundary Conditions Assumed Neumann condition at outskirts, Ñ I' · N = 0 , Enforced by haloing picture with blacks

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Color Shift Mixing disparate pictures Goal: last picture appearance matches input pictures at relating pixels I last (x,y) = c 1 I poisson (x,y) + c 2 Solve  W i (x,y) I unique (x,y) = c 1 I poisson (x,y) + c 2 Each shading channel remade independently

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Outline Context Enhancement Gradient-based Fusion Video Enhancement Surrealism

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Overview of Process Original evening activity camera 320x240 video Day time picture: By averaging 5 seconds of day video Input Output Enhanced video Note: off-ramp, path dividers, structures not unmistakable in unique night video, but rather plainly observed here. Cover outline (for edge above): Encodes pixel with force change

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Algorithm Frame N Gradient field Mixed inclination field TimeAveraged significance veil Processed twofold cover Final outcome Gradient field Frame N-1 Daytime picture

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Outline Context Enhancement Gradient-based Fusion Video Enhancement Related Work Surrealism

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Related Work Spatio-worldly Composition Duchamp ( Nude dropping a staircase ) Freeman 2002 Fels 1999, Klein 2002, Cohen 2003 Gradient-based Techniques Multi-unearthly: Socolinsky 1999 Shadow expulsion: Weiss 2001 High element extend: Fattal 2002 Image altering: Perez 2003 Some at Siggraph'04

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Surrealism Rene Magritte, 'Domain of the Light'

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Outline Context Enhancement Gradient-based Fusion Video Enhancement Surrealism

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Time-slip by Mosaics Maggrite Stripes time

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Time Lapse Mosaic

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Time Lapse Mosaic

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Sunrise at Night

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BiSolar System

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Discussion User Experience More viable in passing on scene setting "Marvelous" appearance Nonrealistic : False conditions Applications Tools for specialists Surveillance Amusement stop rides Performance ~1 sec/outline for 320x240 ~ 3 min for 4Mpixel picture

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Image Fusion for Context Enhancement Nonrealistic however fathomable setting Fusion utilizing numerous pictures Enhancing night pictures with day bgrnd Gradient-based combination Video surrealism instruments t