Real-time structured texture synthesis and editing using image-mesh analogies

Dischler, Jean‐Michel; Zara, Florence

doi:10.1007/s00371-006-0077-4

Cited by 15 publications

(10 citation statements)

References 32 publications

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“…(15) analyze and transform textures into a low-dimensional and Euclidean appearance space. Dischler et al (16) proposed a structured texture synthesis with focus on patterns characterized by structural arrangements. However, these techniques have difficulties in extracting features when ambiguous or low contrast texture features present in sample textures, which are strongly limited by the fact that they rely on texture features to keep structural consistency.…”

Section: Patch-based Texture Synthesismentioning

confidence: 99%

Texture Synthesis based on Feature Description

Gui

Chen

Xie

et al. 2012

JAMDSM

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Patch-based texture synthesis techniques from a small sample texture generate a new texture image efficiently, but one significant problem is that these existing texture synthesis algorithms suffer from structure mismatching across patch boundaries due to inaccurate similarity measure. In this paper, we propose a desired distance metric to measure structural similarity when especially handling textures with salient features, which has the ability to find best matches during the patch-based sampling. To do this, we introduce the concept of "layers" to describe the correlation of pixels through computing each pixel weight, and construct the orientation fields to capture the inherent direction and variation of texture features through computing the dominant local orientation angle and the degree of anisotropy of each pixel. Our experimental results demonstrate that the proposed method can significantly alleviate structure discontinuities in synthesized textures.

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Section: Patch-based Texture Synthesismentioning

confidence: 99%

Texture Synthesis based on Feature Description

Gui

Chen

Xie

et al. 2012

JAMDSM

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“…Besides texture synthesis methods, texture edition methods can also efficiently produce textures [13,14] . They achieve high efficiency by exploiting some regular or easy-edition contents from the input texture.…”

Section: Related Workmentioning

confidence: 99%

Texture synthesis via the matching compatibility between patches

Wang

Liu

Huang

et al. 2009

Sci. China Ser. F-Inf. Sci.

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A new patch-based texture synthesis method is presented in this paper. By the method, a set of patches that can be matched with a sampled patch for growing textures effectively, called the matching compatibility between patches, is generated first for each patch, and the set is further optimized by culling the patches that may cause synthesis conflicts. In this way, similarity measurement calculation for selecting suitable patches in texture synthesis can be greatly saved, and synthesis conflicts between neighbouring patches are substantially reduced. Furthermore, retrace computation is integrated in the synthesis process to improve the texture quality. As a result, the new method can produce high quality textures as texture optimization, the best method to date for producing good textures, and run in a time complexity linear to the size of the output texture. Experimental results show that the new method can interactively generate a large texture in 1024 × 1024 pixels, which is very difficult to achieve by existing methods.texture synthesis, match, texture patch, large textures

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“…Using their formulation, simple parametric models could be constructed from input texture samples to purposefully manipulate the regularity of near-regular textures. The techniques of synthesizing and editing structured textures have also been presented [6]. They assimilate texture images to corresponding 2D geometric meshes, while synthesis is then based on the creation of new vertex/polygon distributions matching some arrangement map.…”

Section: Related Workmentioning

confidence: 99%

“…We use iteratively re-weighted least squares (IRLS), similarly to [12] and [11], to minimize the energy. To this end, we rewrite the terms of the energy functional (5) as follows: (6) and minimize the following quadratic functional:…”

Section: Optimization Phasementioning

confidence: 99%

Perspective-aware texture analysis and synthesis

2008

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The original publication is available at www.springerlink.comInternational audienceThis paper presents a novel texture synthesis scheme for anisotropic 2D textures based on perspective feature analysis and energy optimization. Given an example texture, the synthesis process starts with analyzing the texel (TEXture ELement) scale variations to obtain the perspective map (scale map). Feature mask and simple user-assisted scale extraction operations including slant and tilt angles assignment and scale value editing are applied. The scale map represents the global variations of the texel scales in the sample texture. Then, we extend 2D texture optimization techniques to synthesize these kinds of perspectively featured textures. The non-parametric texture optimization approach is integrated with histogram matching, which forces the global statics of the texel scale variations of the synthesized texture to match those of the example. We also demonstrate that our method is well-suited for image completion of a perspectively featured texture region in a digital photo

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Real-time structured texture synthesis and editing using image-mesh analogies

Cited by 15 publications

References 32 publications

Texture Synthesis based on Feature Description

Texture Synthesis based on Feature Description

Texture synthesis via the matching compatibility between patches

Perspective-aware texture analysis and synthesis

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