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IEEE Transactions on Consumer Electronics
Vol. 21, No.11, November 2012
Zheng Guo Li, Jing Hong Zheng, Susanto Rahardja
Presented by Ji-Heon Lee
School of Electrical Engineering and Computer Science
Kyungpook National Univ.
Detail-Enhanced Exposure Fusion
Abstract
Exposure fusion
– Obtaining pseudo-HDRI without generation of ture HDRI
Proposed method
– Detail-enhanced weight
• Novel quadratic optimization-based method
− Extracting fine details from LDRIs
– Fusion fine details
2/17
Introduction
Tone mapping
– E.Reinhard’s
• Obtaining pseudo-HDR image from true-HDR image
– Farbman’s method
• Correction of filter in Retinnex Theory
− Based on Global Filter
− Based on Edge-Preserving Filter
• General flow
Input image Three detail layers Output luminance
Compression
function Restore color
Filter
3/17
Exposure fusion
– Mertens’ method
• Considering contrast, saturation and well-exposure weight
• Fusion of LDR images using pyramid method
– Zhang’s method
• Using gradient direction for ghost-free
4/17
Overview of proposed method
– Using quadratic optimization-based method
• Obtaining fine details
– Using T.Mertens’ method for restriction of well-pixel
• Contrast, saturation, well-exposedness
• Fusion of LDR images with pyramid method
– Restricting fused image using fine-detail weight
5/17
Detail-enhanced fusion of differently exposed images
Vector field
– Gradient field
– Well-exposure restriction
– Weight factor of gradient vector
1; 127( )
256 ;
z if zz
z otherwise
(1)
( ( , 1) ( , ), ( 1, ) ( , ))k k kY i j Y i j Y i j Y i j
where is luma components.
( , )(1 )kY i j k N
where is weight function. ( )z
,1( , ) ( ( , )) ( ( , 1))k k kW i j Y i j Y i j
,2 ( , ) ( ( , )) ( ( 1, ))k k kW i j Y i j Y i j
(2)
(3)
,1 ,2( ( , ), ( , ))k kY i j Y i j
6/17
– Vector field
• Constructing by weighted average of gradients over all exposures
, ,1
,1
log( ), 1,2
N
k q k qkq N
k qk
q
W Yv
W(4)
where stand for desired vectors,
is vectors of . , ,, ,q k q k qv W Y , ,( , ) ' , ( , ) ' , ( , ) 'q k q k qv i j s W i j s Y i j s1 2( , ) ( ( , ), ( , ))Ti j v i j v i jv
7/17
Fine details weight
22
212
21 2
2 2
min( ) ( )d
dd
d
L
LL vvyxL
v v(5)
where norm, Euclidean distance,
is represents fine details to be extracted at position ,
is vector containing all ,
function selected as ,
is regularization factor which obtaining tradeoff between two terms.
22is l
( , )dL i j ( , )i j
dL ( , ) 'dL i j s
( ) | |z z ( )z
(6)
8/17
– Optimal solution of fine details using following equation
1 2 1 1 2 2( ) ( ) ( ) ( )T T T T
x x y y d x yI D A D D A D D A D A v v L v v v v (7)
where ,and are discrete differentiation operators,
and are and .
xDyD
1( )A v 2( )A v1
1
( ( , ))diag
v i j
2
1
( ( , ))diag
v i j
9/17
T.Mertens’ method for restriction of well-pixel
– Weight sum of LDR images using pyramid method
• Obtaining weight
− Contrast
− Saturation
− Well-exposedness
• Fusing image operation of pyramid level
( , )kC i j
( , )kS i j
( , )kE i j
( , ) ( , ) ( , ) ( , )k k k kW i j C i j S i j E i j
1
{ ( , )} [ { ( , )} { ( , )} ]N
l l l
k k
k
L Z i j L Z i j G W i j
where is weight map Gaussian pyramid,
is Laplacian pyramid of LDR images,
is fusion image Laplacian pyramid.
{ ( , )}l
kG W i j{ ( , )}l
kL Z i j
{ ( , )}lL Z i j
(8)
10/17
Final fusion
– Combining fine detail weight and T.Mertens’ well-pixel weight
int( , ) ( , ) exp( ( , ))f dZ i j Z i j L i j (9)
where is intermediate image generated by T.Mertens’ method. int ( , )Z i j
11/17
Experimental results
Comparison of different selection of
(a) (b) (c)
(d) (e) (f)
(g) (h) (f)
Fig. 1. Comparison of
different selections of λ.
The input images are
captured under the same
lighting conditions. Image
courtesy of Jacques Joffre.
(a) First input image. (b)
Second input image. (c)
Third input image. (d)
Details extracted by λ =
0.25. (e) Details extracted
by λ = 1. (f) Details
extracted by λ = 4. (g) Final
image obtained by λ = 0.25.
(h) Final image
obtained by λ = 1. (i) Final
image obtained by λ = 4. 12/17
Comparison with other methods
– Input image courtesy of “Laurance Meylan”
(a) (b) (c) (d) (e) (f) (g)
(h) (i) (j)
Fig. 2. Comparison of the proposed exposure fusion scheme with two multiple-scale exposure
fusion schemes in [4] and [6]. Image courtesy of Laurance Meylan. (a) First input image. (b)
Second input image. (c) Third input image. (d) Fourth input image. (e) Fifth input image. (f) Sixth
input image. (g) Seventh input image. (h) Final image obtained by the exposure fusion scheme in
[4]. (i) Final image obtained by the proposed fusion algorithm. (j) Final image obtained by the
exposure fusion scheme in [6]. 13/17
– Input image courtesy of “Jacques Joffre”
Fig. 3. Comparison of the proposed exposure fusion scheme with two multiple-scale exposure
fusion schemes in [4] and [6]. Image courtesy of Jacques Joffre. (a) First input image. (b) Second
input image. (c) Third input image. (d) Final image obtained by the exposure fusion scheme in [4].
(e) Final image obtained by the proposed exposure fusion scheme. (f) Final image obtained by
the exposure fusion scheme in [6].
(a)
(a) (b) (c) (d) (e) (f)
14/17
– Input image with flash image
(f) (e) (d)
(c) (b) (a)
Fig. 4. Comparison of the proposed exposure fusion scheme with the HDR
imaging scheme of Photoshop CS5 and the exposure fusion scheme in [4]. (a)
Input image without flash. (b) Input image with flash. (c) Details extracted by
the proposed exposure fusion scheme. (d) Final image obtained by the HDR
imaging scheme in Photoshop CS5. (e) Final image obtained by the proposed
exposure fusion scheme. (f) Final image obtained by the exposure fusion
scheme in [4].
15/17
– Comparison focus on number of lighting resource
(f) (e) (d)
(c) (b) (a)
Fig. 4. Comparison of the proposed exposure fusion scheme with the HDR
imaging schemes of Photoshop CS5 and the exposure fusion scheme in [4]. (a)
Input image with one lighting resource. (b) Input image with two lighting resources.
(c) Input image with three lighting resources. (d) Final image obtained by the HDR
imaging scheme in Photoshop CS5. (e) Final image obtained by the proposed
exposure fusion scheme. (f) Final image obtained by the exposure fusion scheme
in [4]. 16/17
Proposed method
– Obtaining displayable HDR image without tonemapping
– Novel quadratic optimization-based method
• Extracting fine details from LDRIs
– Fusion fine details
Experimental results
– Detail enhancement
• More pleasing resulting than previous methods
Conclusions
17/17
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