Texture Synthesis Method for Generic Video Sequences

2014 ◽

Vol 571-572 ◽

pp. 825-828

Author(s):

Xiang Zhang ◽

Jun Hua Wang ◽

Xiao Ling Xiao

Keyword(s):

Local Search ◽

Texture Synthesis ◽

Synthesis Method ◽

Image Inpainting ◽

Search Method ◽

Local Search Method ◽

Synthesis Algorithm ◽

Image Construction ◽

Tv Model ◽

Improved Algorithm

The image inpainting method based on CriminiciA’s algorithm is slowly complete the image for large blank area. An improved algorithm based on the classic texture synthesis algorithm for image inpainting is proposed for imaging logging inpainting, which is used to generate the fullbore image. Two schemes, the local search method and priority calculation with TV model, are employed in the improved texture synthesis method. Some examples were given to demonstrate the effectiveness of the proposed algorithm on dealing with fullbore image construction with large blank area and raising efficiency obviously.

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A video texture synthesis method based on wavelet transform

2007 International Conference on Wavelet Analysis and Pattern Recognition ◽

10.1109/icwapr.2007.4421611 ◽

2007 ◽

Cited By ~ 1

Author(s):

Jun-Yu Dong ◽

Chun-Xia Zhang ◽

Yu-Juan Wang ◽

Hui-Yu Zhou

Keyword(s):

Wavelet Transform ◽

Texture Synthesis ◽

Synthesis Method

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Structure Preserving Exemplar-Based 3D Texture Synthesis

10.20948/graphicon-2021-3027-433-442 ◽

2021 ◽

Author(s):

Andrew Babichev ◽

Vladimir Alexandrovich Frolov

Keyword(s):

Neural Network ◽

3D Model ◽

Texture Synthesis ◽

Error Function ◽

Synthesis Method ◽

Structural Elements ◽

The Third ◽

3D Texture ◽

Additional Image ◽

Network Approaches

In this paper we propose exemplar-based 3D texture synthesis method which unlike existing neural network approaches preserve structural elements in texture. The proposed approach does this by accounting additional image properties which stand for the preservation of the structure with the help of a specially constructed error function used for training neural networks. Thanks to the proposed solution we can apply 2D texture to any 3D model (even without texture coordinates) by synthesizing high quality 3D texture and using local or world space position of surface instead 2D texture coordinates (fig. 1). Our solution is based on introducing 3 different error components in to the process of neural network fitting which helps to preserve desired properties of generated texture. The first component is for structuredness of the generated texture and the sample, the second component increases the diversity of the generated textures and the third one prevents abrupt transitions between individual pixels.

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Hepatic Texture Synthesis Method Based on the Accelerated CUDA

Recent Advances in Intelligent Information Hiding and Multimedia Signal Processing - Smart Innovation, Systems and Technologies ◽

10.1007/978-3-030-03748-2_31 ◽

2018 ◽

pp. 249-256

Author(s):

Lin Xu ◽

Na Wang ◽

Chao-Fan Xie ◽

Lu-Xiong Xu ◽

Fuquan Zhang

Keyword(s):

Texture Synthesis ◽

Synthesis Method

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A Novel Image Inpainting Method Based on Sparse Decomposition

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.738-739.573 ◽

2015 ◽

Vol 738-739 ◽

pp. 573-577

Author(s):

Xuan Zhu ◽

Xu Feng Zhang ◽

Qiu Ju Li ◽

Ji Yao Tao ◽

Ben Yuan Li

Keyword(s):

Texture Synthesis ◽

Synthesis Method ◽

Image Inpainting ◽

Discrete Wavelet ◽

Sparse Decomposition ◽

Component Decomposition ◽

Morphological Component ◽

Curvature Driven ◽

Different Characteristics ◽

Redundant Discrete Wavelet Transform

Redundant Discrete Wavelet Transform (RDWT) and Wavelet Atomic Transform (WAT) are proposed in this paper as a couple of dictionaries to get the structure and texture basing on morphological component decomposition. Then, basing on the fact that the structure and texture have different characteristics, in this paper we use curvature driven diffusion model and Criminisi texture synthesis method to inpaint the structure and texture respectively. At last, compound the inpainted structure and texture and get the inpainting result. The experiment results show the new method can not only decompose the image very well, but also inpaint the image with strong and fairing edge, complete and clear texture .This method shows better results in image inpainting compared to the classical ones.

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