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A. I. P
9512514 郭瓊蓮 922014 柯瑋明 922508 吳榮軒
Term Project
• Implement this paper :“Two-scale Tone Management
for photographic Look,” Bae, Paris, and Durand.
• Apply the method to different kind of pictures.
• Add HDR technique.
Subject Review
Algorithm Review
model
input
base
detail
bilateral filter
high pass and local averaging textureness
texturenesstransfer
large-scaletransfer
Algorithm Reviewmodified base
modified detail
final output
constrained combination
postprocess
black-and-whiteoutput
Our works
Our input
Our model
Our works
Our detail
Our base
Our works
With edge preserving
Without edgepreserving
Our works
Our result
Author’s result
HDR
HDR
• Uncertainty.• Poisson equation.• Histogram matching.• Textureness.• Color channel.
Problems
• An old problem while using fast bilateral filter.
Uncertainty
Uncertainty
• Cost most time in our pipeline.
• Use Discrete Sine Transform to reduce time complexity.
• Easy to implement.
Poisson
• General Poisson Equation:– Ixx + Iyy = f
• For discrete version, we can rewrite the equation to matrix form:– TI + IT = F ,where T is a N*N triagonal matrix of
{1,-2,1}.
Poisson
• We define
SXS I
I2
1NS SS
SDTS
),...,diag( D
],...ss,[s S 2
1Nss
22N
j4sin where,s Ts
] 1N
N,...sin
1N
2sin,
1N[sins
2T
N21
N21
jkkTj
2jjjj
Tj
Poisson
Poisson
BSFS1N
2XDDX
SFSDXSSDXSS
SFSXSTSSSTSXS
FSXSTTSXS
FITTI
2
2222
22
• DX+XD=B is easy to solve
• Then we use I=SXS to get final answer.
Poisson
)/(bx
bxx
kjjkjk
jkkjkjkj
• In fact, SXS performs 2-D DST on X
• Implementation steps:– Perform 2-D DST on F– Divide the sum of the correspondin
g eigenvalue and a constant.– Perform 2-D DST again
Poisson
• The gray-value in log domain are always negative or zero.
• The range could be even wider if HDR added.
• The function implemented by MATLAB can only handle the interval from 0 to 1……
Hist-matching
Hist-matching
Inputdistribution
histogram
Hist-matching
Mask
distribution
histogram
Hist-matching
Outputdistribution
histogram
Hist-matching
Input
Output
Mask
Textureness
ρp = max( 0, ( T’p – T(B’)p ) / T(D)p )
T( I )p = 1/k * ∑ gσs( |p – q| ) gσr( |Ip - Iq| )|H|q
q∈|H|
k = ∑ gσs( |p – q| ) gσr( |Ip - Iq| ) q∈I
O = B’ + ρD
H is the high-pass version of the image.
Textureness
Input
Textureness
High frequency of H
Textureness
Absolute value of H
Textureness
T
Textureness
0 +
Textureness
• Which color channel could work best?
– RGB channel.• Process separately.• Process intensity only and then
interpolate the three channel.
– YUV channel.
Color Channel
Color Channel
Color Channel
Color Channel
Color Channel
More Images
Input Model
More Images
Input Output
More Images
Input
Model
More Images
Input Output
More Images
Input
Model
More Images
Input
Output
More Images
Input
Model
More Images
Input
Output
QuestionsThanks for your attention.
