多带融合法：创建高质量图像纹理贴图的新方法

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"Seamless Image-Based Texture Atlases using Multi-band Blending" 是一篇关于纹理贴图领域的研究论文，着重于解决从三维模型和校准图像创建高质量无缝纹理贴图的问题。传统上，由于摄影测量和几何精度的不准确，可能会在纹理边界出现颜色断层、鬼影（ghosting）或模糊现象，这些问题严重影响了视觉效果的连贯性。论文首先提出了一种新颖的方法，通过计算网格面的划分，实现了视觉细节和颜色连续性的良好平衡。利用图割优化技术，他们高效地确定了接近最优的接缝位置，确保了纹理在不同部分之间的平滑过渡。这种方法在保持视觉效果的同时，减少了色彩不一致带来的问题。接着，作者引入了基于多带图像融合的三维扩展原理，对接缝附近的像素进行颜色校正。这种技术能够实现无瑕疵的颜色连续性，同时避免了鬼影等常见问题。这种方法的核心在于细致地处理颜色空间的混合，通过分段处理不同频段的信息，保证了颜色在空间上的平滑过渡，从而提高了整个纹理贴图的整体质量。论文的重点实验部分展示了他们的方法在两个大型真实场景中的应用效果，通过实际案例展示了其在实际项目中的可行性和优越性。无缝纹理贴图的应用广泛，例如游戏开发、虚拟现实、建筑设计等领域，提高贴图质量和效率对于提升沉浸式体验至关重要。总结来说，这篇论文提供了一种创新的纹理贴图技术，通过结合高效的接缝优化和细致的多带融合策略，解决了传统方法中存在的视觉问题，为高质量的无缝纹理贴图生成开辟了新的途径。这对于提升数字内容的逼真度和用户感知有着显著的推动作用。

Seamless Image-Based Texture Atlases using Multi-band Blending

edric All

ene, Jean-Philippe Pons and Renaud Keriven

CERTIS,

Ecole des ponts, Paris-Est, France

{allene,pons,keriven}@certis.enpc.fr

Abstract

In this paper, we propose a novel method for creating

a high-quality texture atlas from a 3D model and a set

of calibrated images. Our method focuses on avoiding

visual artifacts such as color discontinuities, ghosting

or blurring, which typically arise from photometric and

geometric inaccuracies. We ﬁrst compute a partition of

mesh faces which realizes a good trade-off between vi-

sual detail and color continuity at patch boundaries: we

efﬁciently obtain a close-to-optimal seam placement us-

ing graph cuts optimization. We then apply a pixel-wise

color correction in the vicinity of patch boundaries with

a principled 3D extension of multi-band image blend-

ing: we achieve faultless color continuity while avoid-

ing ghosting artifacts. We demonstrate the effectiveness

of our method on two real-world large-scale scenes.

1. Introduction

Capturing, processing and displaying the visual at-

tributes, such as color, of a 3D model typically requires

to map its surface to a two-dimensional domain. Gen-

erally, it is impossible to ﬁnd a global such parameter-

ization with acceptable distortion, so an atlas structure

is adopted: it consists of a partition of the surface into

connected parts (patches) and of a piecewise 2D param-

eterization (cf for example [16] and references therein).

The instantiation of this problem in the context of

image-based 3D modeling, i.e. when extracting geom-

etry and/or visual attributes from digital photographs,

has received much attention in the computer vision and

computer graphics communities.

On the one hand, the image-based case alleviates

the parameterization problem: the projective transfor-

mations from the surface to the input images constitute

natural and optimal mappings [11, 17, 19]. They avoid

image resampling and loss of visual detail, contrarily to

approaches based on other parameterizations [1, 2, 7].

On the other hand, in the image-based modeling con-

text, color discontinuities at patch boundaries (seams)

are a crucial issue, due to photometric and geometric in-

accuracies: varying lighting conditions and camera re-

sponse, non-Lambertian reﬂectance, imperfect camera

calibration, approximate shape, etc. Weighted averag-

ing of images in overlapping regions [2, 6, 12, 14, 17]

is not sufﬁcient. It causes unsatisfactory ghosting

and blurring, unless the 3D model is highly accurate

(e.g. obtained by laser range scanning) and camera

calibration is tightened using image-based registration

[2, 8, 12].

Two main axes of research have been explored in

order to reduce seam visibility. The ﬁrst approach is

the optimization of patch layout. Some works force

patch boundaries into regions of high negative curva-

ture [13, 18]. Others use an image ﬁdelity term [11, 20]

to explicitly look for a partition of the surface induc-

ing minimal color discontinuities. Of particular interest

is the formulation of this problem as a Markov random

ﬁeld optimization [11], for it brings powerful algorith-

mic tools into play. However, these works suffer from

the absence of per-pixel processing: they are unable to

achieve perfect color continuity.

The second improvement path is precisely pixel-wise

color correction in the vicinity of patch boundaries. A

notable work in this category is a tentative extension of

2D multi-band image splining [5] to textured 3D sur-

faces [1]. However, this work misses the importance

of an optimal patch layout, and fails to deﬁne transition

zones of distinct and adapted width for the different fre-

quency bands. As a result, it has to keep to a two-band

frequency decomposition to limit ghosting artifacts.

In this paper, we propose a novel method for creating

a high-quality seamless texture atlas from a 3D model

and a set of calibrated images. Our method upgrades the

Markov random ﬁeld approach of [11] with a principled

3D extension of multi-band image blending, thereby

achieving both close-to-optimal seam placement and

faultless color continuity. We demonstrate the effective-

ness of our method on two real-world large-scale scenes

reconstructed from high-resolution images using recent

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