enhancement of backlight scaled images
TRANSCRIPT
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ENHANCEMENT OF BACKLIGHT SCALED IMAGES
P. VIBHA BHANDARY4SF10EC101
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INTRODUCTION
Goal- to reduce undesired effects of dim backlight on image quality with backlight 10% or less.
Human Visual System( HVS)- a perception based approach.
Luminance < threshold => image detail invisibility
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INTRODUCTION
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BACKGROUND
1) Just Noticeable Difference (JND):
1. Linear curve-behavior
2. Smallest difference in the sensory input discernible by human being.
3. ΔL= J(L)=0.0594(1.219+L 0.4 )2.5
L= Background luminance
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2) Human Visual Response Model:
1. Nonlinear curve-behavior
2. Li= Li-1 +J( Li-1) , L>0
3. Li reaches upper bound of luminance range
3) Effects of dim backlight on images:
V/Vm = normalized response
I=Perceived light intensity
σ= half saturation parameter
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APPROACHES
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PROPOSED ALGORITHM
1) Prediction of the Detail Loss Effect
PL= PLF (1-PL
D )
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2) Enhancement of invisible pixels
JND Decomposition:
E= 2D tan (2.5 π/180)
Luminance Boosting and Compression:
Color Restoration:
Compensation for the Halo Effect
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PERFORMANCE EVOLUTION
ABIE: Adaptive Backlight Image Enhancement
CBCS: Concurrent Brightness Contrast Scaling
TABS: Temporally aware backlight scaling
GD: Gradient Domain
Subjective Evaluation
Objective Evaluation
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Visualization
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CONCLUSION
Algorithm effectively
1. enhances the visibility of image dark region.
2. applies counter shading to eliminate halo effect.
3. enhances perceptual contrast of bright regions.
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“A goal is not always meant to be reached. But often something to aim at”
-Bruce Lee