Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Image quilting for texture synthesis and transfer
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Transferring color to greyscale images
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
IEEE Computer Graphics and Applications
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
EGRW '03 Proceedings of the 14th Eurographics workshop on Rendering
Image analysis by analogy with Taylor expansion
Proceedings of the 20th spring conference on Computer graphics
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Automated colour grading using colour distribution transfer
Computer Vision and Image Understanding
Image and Video Colorization Using Vector-Valued Reproducing Kernel Hilbert Spaces
Journal of Mathematical Imaging and Vision
Image coding based on a fractal theory of iterated contractive image transformations
IEEE Transactions on Image Processing
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The Taylor expansion has shown in many fields to be an extremely powerful tool. In this paper, the authors investigated image features and their relationships by analogy with Taylor expansion. The kind of expansion could be helpful for analyzing image feature and engraftment, such as transferring color between images. By analogy with Taylor expansion, the image color transfer algorithm is designed by the first and second-order information. The luminance histogram represents the first-order information of image, and the co-occurrence matrix represents the second-order information of image. Some results illustrate the proposed algorithm is effective. In this study, each polynomial in the Taylor analogy expansion of images is considered as one of image features which help in re-understanding images and its features. By using the proposed technique, the features of image, such as color, texture, dimension, time series, would be not isolated but mutual relational based on image expansion.