Search

Copyright of Journal of Computer-Aided Design & Computer Graphics / Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problems of patch-based synthesis algorithm of structured texture images,such as discontinuity of structure,distortion of boundary,seam misalignment,and low synthesis speed,a new fast non-overlapping synthesis algorithm of texture images is proposed based on the consistency criterion of double-seam lines,thereby effectively improving the synthesis quality and speed of structured texture images.Firstly,the seamline consistency criterion considering hue,saturation,brightness and edge characteristics simultaneously is established in HSI color space that is more consistent with human visual characteristic.Then,a sub-block search strategy and a new non-overlapping splicing algorithm based on the consistency criterion of double-seam line are proposed and implemented.The experiment results show that the proposed algorithm can significantly improve the synthesis quality and speed of structured texture images in comparison with the traditional algorithms.

Copyright of Journal of Jilin University (Science Edition) / Jilin Daxue Xuebao (Lixue Ban) is the property of Zhongguo Xue shu qi Kan (Guang Pan Ban) Dian zi Za zhi She and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the texture synthesis in new computer graphics technical conditions, this paper proposed a texture interpolation method to synthesize different resolution textures adaptively from a single real world texture. The synthesized texture's DPI was the same as the original texture example. Firstly, the proposed method used a high-dimensional interpolation algorithm to generate an intermediate guidance texture with target resolution by split the source texture. Secondly, it selected particular random patches to fill the gaps in the intermediate texture according to the self-similarity in the source texture. Finally, it seamlessly embedded these patches in the previous intermediate texture by the Poisson image-editing algorithm. Experimental results show that the proposed method can handle both stationary and non-stationary texture synthesis, and the synthetic results are more consistent in the visual properties of the source texture. In addition, the implement logic of the proposed method is enough simple to be programing and executing on a common mobile platform. [ABSTRACT FROM AUTHOR]

The calculation of the priority of the pixel to be repaired and the determination of the best matching block are based on two basic steps of the texture synthesis image inpainting method.The traditional method is not suitable because it is difficult to determine the confidence in the priority calculation,and it is difficult to search for the best matching block.An image inpainting method based on weighted priority and classification matching was proposed.In the priority model,the exponential function and the normalization function were introduced to optimize the confidence and data items separately,the further benefit of which was a more objective priority of calculation and a more reasonable repair order.Based on the proposed functions,the structure information was used as a measure factor of the search matching block,and the best matching block was selected by the classification and screening method.Experimental results show that the proposed method can shorten the repair time under the condition of obtaining good repair effect.

In order to improve the embedded capacity and anti-interference capability of the coverless steganography algorithm, this paper proposes a texture synthesis information hiding scheme based on LBP texture analysis. Firstly, the original small-size texture image is selected and divided into uniform pixel blocks, the LBP value of each pixel in the image blocks is calculated, and the LBP value with the largest LBP distribution is taken as the representive information of the image block. Secondly, when hiding the secret information, the pseudo-random sequence is generated with a specified key to determine the position of the texture candidate block placed on the white paper, then the candidate block is selected according to the value of the secret information and placed on the designated position on the white paper, and the remaining blank areas are filled by the texture synthesis method. Inversely, when extracting secret information, the position of the steganography image block is obtained according to the pseudo-random sequence generated by the key, then the LBP value of each image block with the largest distribution is calculated to obtain the secret information. Experimental results show that the steganography image generated by this method has good visual effect and further improves the embedded capacity and anti-interference ability. [ABSTRACT FROM AUTHOR]

In order to promote the technology research of image style transfer based on deep learning, and discussed the current major methods and representative work. Firstly,this paper reviewed the non-transfer, and introduced the basic principles and methods of image style transfer based on deep learning plication prospect of image style transfer technology in related fields. At last, this paper summarized tin future research directions of image style transfer based on deep learning. [ABSTRACT FROM AUTHOR]

A discontinuously transitional color appears in the connection part between different planes when 2D digital camouflage pattern is applied on a 3D target surface. To solve this problem, a digital camouflage stitching method is proposed based on texture synthesis and best seam line algorithm. The tex¬ture synthesis technology is used to create naturally transitional extended digital camouflage pattern, thus constructing a fake overlap region for digital camouflage pattern, and searching the best seam line in the overlap region. And then the patterns to be stitiched are tailored and stitched together to achieve the seamless stitching of digital camouflage pattern. The qualitative and quantitative methods are used to eva¬luate the stitching result. Experimental results show that the proposed method can effectively eliminate the significant gaps in stitched camouflage pattern, and make it more natural. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) sensors can work at all times and under all weather conditions，but SAR images are less intuitive and more difficult to understand. To complement advantages of optical and SAR sensors, a technique of image translation is put forward. Firstly, the definition of remote sensing image translation is presented. Then, some specific solutions for image understanding, and object transformation which are considered as key steps for image translation are proposed. Feature extraction, Support Vector Machine classification, and sample-based texture synthesis algorithms are adopted to translate typical classes of SAR data into optical images. Finally, two kinds of SAR images with different resolution are translated into Landsat TM and GeoEye images respectively, and the translated result could be applied to fill the blanks in those incomplete optical images. Overall, the research indicates that the proposed techniques of image translation from SAR to optical data are rational and effective. [ABSTRACT FROM AUTHOR]

Objective An image inpainting algorithm based on combination of wavelet transform and texture synthesis is discussed to overcome the error repair of the boundary of structure and texture in traditional image inpainting algorithm. The discussed image inpainting algorithm utilizes characters of wavelet transform domain coefficients. Wavelet transform has been used as a good image representation analysis in addition to statistical properties. Multiresolution analysis of wavelet transform is helpful to predict coarse-to-fine image structure. In particular, texture and detailed patterns for natural images must be analyzed. Wavelet can treat these elements altogether. In view of the advantages of image decomposition algorithm, wavelet coefficient statistical properties, and visual effect of edge information of an image, we proposed an image inpainting algorithm based on combination of wavelet transform and texture synthesis. Method Our reconstruction modeling is based on classical image decomposition model. Some actions have been taken to improve reconstruction performance. An image can be seen as a combination of texture and structure. Thus, the image repair process should fully consider the texture and structural characteristics of an image. At first, the damaged image is decomposed into low-frequency sub-image and high-frequency sub-image with different resolutions via wavelet transformation. In cases where low-frequency component represents image structure, high-frequency component reflects edge changes of an image. Moreover, low-frequency component has a positional correspondence relationship with high-frequency component. Then, sub-images are reconstructed in accordance with their respective characteristics. The sub-image that reflects structural information of an image is reconstructed with fast multipole method, whereas the sub-image that reflects texture information of an image is filled in with texture synthesis based on the characteristics of wavelet coefficient in sub-images . We introduce edge factor in combination with the characters of the wavelet transform domain coefficients to update priority function in the process of reconstituting high-frequency sub-images. Finally, the recovered sub-images are reconstructed with wavelet. Result Simulation results show that this hierarchical classification method works well in edge damaged blocks. The power signal-to-noise ratio of the final result compared with the traditional algorithm has been improved by approximately 1 dB to 2 dB. The repair results are consistent with human visual perception. Conclusion Image decomposition model is a widely used image inpainting method. However, fuzzy and mismatching can be generated easily during the repair process. Therefore, when high-frequency component is repaired, changes in factor coefficients of high-frequency components must be introduced to enable the repair process be in accordance with edge direction. In such case, repairing image edge and improving matching block search are top priorities to reduce mismatch error . The proposed method can eliminate point defects in the repair process. Compared with the related algorithms, our algorithm holds good integrated performance. It can effectively repair damaged image with strong edges and rich texture, particularly for the loss scenarios and natural images, to improve image inpainting quality and to be consistent with human visual effects. [ABSTRACT FROM AUTHOR]