LNCS 3024 Seamless Image Stitching in the
Gradient Domain 1st edition by Anat Levin, Assaf
Zormet, Shrmuel Peleg, Yair Weiss ISBN
3540219811 978-3540219811 pdf download
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in-the-gradient-domain-1st-edition-by-anat-levin-assaf-zormet-
shrmuel-peleg-yair-weiss-isbn-3540219811-978-3540219811-13856/
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LNCS 3024 Transformation Invariant Embedding for Image Analysis 1st
edition by Ali Ghodsi, Jiaytian Huang, Dale Schuurmans ISBN 3540219811
978-3540219811
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embedding-for-image-analysis-1st-edition-by-ali-ghodsi-jiaytian-
huang-dale-schuurmans-isbn-3540219811-978-3540219811-14006/
LNCS 3024 Multiphase Dynamic Labeling for Variational Recognition-
Driven Image Segmentation 1st edition by Daniel Cremers, Nir Sochen,
Christoph Schnorr ISBN 3540219811 978-3540219811
https://ebookball.com/product/lncs-3024-multiphase-dynamic-
labeling-for-variational-recognition-driven-image-
segmentation-1st-edition-by-daniel-cremers-nir-sochen-christoph-
schnorr-isbn-3540219811-978-3540219811-11458/
LNCS 3024 Reliable Fiducial Detection in Natural Scenes 1st edition by
David Claus, Andrew Fitzgiblon ISBN 3540219811 978-3540219811
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detection-in-natural-scenes-1st-edition-by-david-claus-andrew-
fitzgiblon-isbn-3540219811-978-3540219811-11374/
User Assisted Separation of Reflections from a Single Image Using a
Sparsity Prior 1st edition by Anat Levin, Yair Weiss ISBN 3540219842
9783540219842
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reflections-from-a-single-image-using-a-sparsity-prior-1st-
edition-by-anat-levin-yair-weiss-
isbn-3540219842-9783540219842-13860/
,LNCS 3024 Stereovision Based Head Tracking Using Color and Ellipse
Fitting in a Particle Filter 1st edition by Bogdan Kwolek ISBN
3540219811 978-3540219811
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tracking-using-color-and-ellipse-fitting-in-a-particle-
filter-1st-edition-by-bogdan-kwolek-
isbn-3540219811-978-3540219811-12932/
LNCS 3024 Tracking People with a Sparse Network of Bearing Sensors 1st
edition by Rahimi, Dunagan, Darrell ISBN 3540219811 978-3540219811
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sparse-network-of-bearing-sensors-1st-edition-by-rahimi-dunagan-
darrell-isbn-3540219811-978-3540219811-14496/
LNCS 3024 Morphological Operations on Matrix Valued Images 1st
edition by Bernhard Burgeth, Martin Welk, Christian Feddern, Joachim
Weickert ISBN 3540219811 978-3540219811
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on-matrix-valued-images-1st-edition-by-bernhard-burgeth-martin-
welk-christian-feddern-joachim-weickert-
isbn-3540219811-978-3540219811-13114/
LNCS 3024 Monocular 3D Reconstruction of Human Motion in Long Action
Sequences 1st edition by Gareth Loy, Martin Eriksson, Josephine
Sullivan, Stefan Carlsson ISBN 3540219811 978-3540219811
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reconstruction-of-human-motion-in-long-action-sequences-1st-
edition-by-gareth-loy-martin-eriksson-josephine-sullivan-stefan-
carlsson-isbn-3540219811-978-3540219811-10088/
LNCS 3024 - Light Field Appearance Manifolds 1st edition by Chris
Mario Chiristoudias, Louis Philippe Morency and Trevor Darrell ISBN
3540219811 Â 978-3540219811
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manifolds-1st-edition-by-chris-mario-chiristoudias-louis-
philippe-morency-and-trevor-darrell-
isbn-3540219811-978-3540219811-11920/
, Seamless Image Stitching in the Gradient
Domain
Anat Levin, Assaf Zomet , Shmuel Peleg, and Yair Weiss
School of Computer Science and Engineering
The Hebrew University of Jerusalem
91904, Jerusalem, Israel
{alevin,peleg,yweiss}@cs.huji.ac.il,
Abstract. Image stitching is used to combine several individual im-
ages having some overlap into a composite image. The quality of image
stitching is measured by the similarity of the stitched image to each of
the input images, and by the visibility of the seam between the stitched
images.
In order to define and get the best possible stitching, we introduce several
formal cost functions for the evaluation of the quality of stitching. In
these cost functions, the similarity to the input images and the visibility
of the seam are defined in the gradient domain, minimizing the disturbing
edges along the seam. A good image stitching will optimize these cost
functions, overcoming both photometric inconsistencies and geometric
misalignments between the stitched images.
This approach is demonstrated in the generation of panoramic images
and in object blending. Comparisons with existing methods show the
benefits of optimizing the measures in the gradient domain.
1 Introduction
Image stitching is a common practice in the generation of panoramic images and
applications such as object insertion, super resolution [1] and texture synthesis
[2]. An example of image stitching is shown in Figure 1. Two images I1 ,I2 capture
different portions of the same scene, with an overlap region viewed in both
images. The images should be stitched to generate a mosaic image I. A simple
pasting of a left region from I1 and a right region from I2 produces visible
artificial edges in the seam between the images, due to differences in camera
gain, scene illumination or geometrical misalignments.
The aim of a stitching algorithm is to produce a visually plausible mosaic
with two desirable properties: First, the mosaic should be as similar as possible
to the input images, both geometrically and photometrically. Second, the seam
between the stitched images should be invisible. While these requirements are
This research was supported (in part) by the EU under the Presence Initiative
through contract IST-2001-39184 BENOGO.
Current Address: Computer Science Department, Columbia University, 500 West
120th Street, New York, NY 10027
T. Pajdla and J. Matas (Eds.): ECCV 2004, LNCS 3024, pp. 377–389, 2004.
c Springer-Verlag Berlin Heidelberg 2004
Gradient Domain 1st edition by Anat Levin, Assaf
Zormet, Shrmuel Peleg, Yair Weiss ISBN
3540219811 978-3540219811 pdf download
https://ebookball.com/product/lncs-3024-seamless-image-stitching-
in-the-gradient-domain-1st-edition-by-anat-levin-assaf-zormet-
shrmuel-peleg-yair-weiss-isbn-3540219811-978-3540219811-13856/
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, Get Your Digital Files Instantly: PDF, ePub, MOBI and More
Quick Digital Downloads: PDF, ePub, MOBI and Other Formats
LNCS 3024 Transformation Invariant Embedding for Image Analysis 1st
edition by Ali Ghodsi, Jiaytian Huang, Dale Schuurmans ISBN 3540219811
978-3540219811
https://ebookball.com/product/lncs-3024-transformation-invariant-
embedding-for-image-analysis-1st-edition-by-ali-ghodsi-jiaytian-
huang-dale-schuurmans-isbn-3540219811-978-3540219811-14006/
LNCS 3024 Multiphase Dynamic Labeling for Variational Recognition-
Driven Image Segmentation 1st edition by Daniel Cremers, Nir Sochen,
Christoph Schnorr ISBN 3540219811 978-3540219811
https://ebookball.com/product/lncs-3024-multiphase-dynamic-
labeling-for-variational-recognition-driven-image-
segmentation-1st-edition-by-daniel-cremers-nir-sochen-christoph-
schnorr-isbn-3540219811-978-3540219811-11458/
LNCS 3024 Reliable Fiducial Detection in Natural Scenes 1st edition by
David Claus, Andrew Fitzgiblon ISBN 3540219811 978-3540219811
https://ebookball.com/product/lncs-3024-reliable-fiducial-
detection-in-natural-scenes-1st-edition-by-david-claus-andrew-
fitzgiblon-isbn-3540219811-978-3540219811-11374/
User Assisted Separation of Reflections from a Single Image Using a
Sparsity Prior 1st edition by Anat Levin, Yair Weiss ISBN 3540219842
9783540219842
https://ebookball.com/product/user-assisted-separation-of-
reflections-from-a-single-image-using-a-sparsity-prior-1st-
edition-by-anat-levin-yair-weiss-
isbn-3540219842-9783540219842-13860/
,LNCS 3024 Stereovision Based Head Tracking Using Color and Ellipse
Fitting in a Particle Filter 1st edition by Bogdan Kwolek ISBN
3540219811 978-3540219811
https://ebookball.com/product/lncs-3024-stereovision-based-head-
tracking-using-color-and-ellipse-fitting-in-a-particle-
filter-1st-edition-by-bogdan-kwolek-
isbn-3540219811-978-3540219811-12932/
LNCS 3024 Tracking People with a Sparse Network of Bearing Sensors 1st
edition by Rahimi, Dunagan, Darrell ISBN 3540219811 978-3540219811
https://ebookball.com/product/lncs-3024-tracking-people-with-a-
sparse-network-of-bearing-sensors-1st-edition-by-rahimi-dunagan-
darrell-isbn-3540219811-978-3540219811-14496/
LNCS 3024 Morphological Operations on Matrix Valued Images 1st
edition by Bernhard Burgeth, Martin Welk, Christian Feddern, Joachim
Weickert ISBN 3540219811 978-3540219811
https://ebookball.com/product/lncs-3024-morphological-operations-
on-matrix-valued-images-1st-edition-by-bernhard-burgeth-martin-
welk-christian-feddern-joachim-weickert-
isbn-3540219811-978-3540219811-13114/
LNCS 3024 Monocular 3D Reconstruction of Human Motion in Long Action
Sequences 1st edition by Gareth Loy, Martin Eriksson, Josephine
Sullivan, Stefan Carlsson ISBN 3540219811 978-3540219811
https://ebookball.com/product/lncs-3024-monocular-3d-
reconstruction-of-human-motion-in-long-action-sequences-1st-
edition-by-gareth-loy-martin-eriksson-josephine-sullivan-stefan-
carlsson-isbn-3540219811-978-3540219811-10088/
LNCS 3024 - Light Field Appearance Manifolds 1st edition by Chris
Mario Chiristoudias, Louis Philippe Morency and Trevor Darrell ISBN
3540219811 Â 978-3540219811
https://ebookball.com/product/lncs-3024-light-field-appearance-
manifolds-1st-edition-by-chris-mario-chiristoudias-louis-
philippe-morency-and-trevor-darrell-
isbn-3540219811-978-3540219811-11920/
, Seamless Image Stitching in the Gradient
Domain
Anat Levin, Assaf Zomet , Shmuel Peleg, and Yair Weiss
School of Computer Science and Engineering
The Hebrew University of Jerusalem
91904, Jerusalem, Israel
{alevin,peleg,yweiss}@cs.huji.ac.il,
Abstract. Image stitching is used to combine several individual im-
ages having some overlap into a composite image. The quality of image
stitching is measured by the similarity of the stitched image to each of
the input images, and by the visibility of the seam between the stitched
images.
In order to define and get the best possible stitching, we introduce several
formal cost functions for the evaluation of the quality of stitching. In
these cost functions, the similarity to the input images and the visibility
of the seam are defined in the gradient domain, minimizing the disturbing
edges along the seam. A good image stitching will optimize these cost
functions, overcoming both photometric inconsistencies and geometric
misalignments between the stitched images.
This approach is demonstrated in the generation of panoramic images
and in object blending. Comparisons with existing methods show the
benefits of optimizing the measures in the gradient domain.
1 Introduction
Image stitching is a common practice in the generation of panoramic images and
applications such as object insertion, super resolution [1] and texture synthesis
[2]. An example of image stitching is shown in Figure 1. Two images I1 ,I2 capture
different portions of the same scene, with an overlap region viewed in both
images. The images should be stitched to generate a mosaic image I. A simple
pasting of a left region from I1 and a right region from I2 produces visible
artificial edges in the seam between the images, due to differences in camera
gain, scene illumination or geometrical misalignments.
The aim of a stitching algorithm is to produce a visually plausible mosaic
with two desirable properties: First, the mosaic should be as similar as possible
to the input images, both geometrically and photometrically. Second, the seam
between the stitched images should be invisible. While these requirements are
This research was supported (in part) by the EU under the Presence Initiative
through contract IST-2001-39184 BENOGO.
Current Address: Computer Science Department, Columbia University, 500 West
120th Street, New York, NY 10027
T. Pajdla and J. Matas (Eds.): ECCV 2004, LNCS 3024, pp. 377–389, 2004.
c Springer-Verlag Berlin Heidelberg 2004
