Deterministic Texture Analysis and Synthesis Using Tree Structure Vector Quantization
نویسنده
چکیده
Texture analysis and synthesis is very important for computer graphics, vision, and image processing. This paper describes an algorithm which can produce new textures with a matching visual appearance from a given example image. Our algorithm is based on a model that characterizes textures using a nonlinear deterministic function. During analysis, an example texture is summarized into this function using tree structure vector quantization. An output texture, initially random noise, is then synthesized from this estimated function. Compared to existing approaches, our algorithm can efficiently generate a wide variety of textures. The effectiveness of our approach is demonstrated using standard test images from the Brodatz texture album.
منابع مشابه
Antipole Clustering for Fast Texture Synthesis
This paper describes a new method for analysis/synthesis of textures using a non-parametric multi-resolution approach able to reproduce efficiently the generative stochastic process of a wide class of real texture images. This is realized through a new data structure the Antipole Tree and a suitable research strategy able to outperform both the classical linear full-search heuristic and the TSV...
متن کاملTexture Synthesis using TSVQ and Target Re-synthesis
This paper presents a simple texture synthesis method that is fast, efficient, and optimized. Given an input texture, the algorithm will synthesize a texture image of specified size by matching output image pixel neighborhoods with input pixel neighborhoods. The pixel-neighborhood matching will be aided by the use of a TreeStructured Vector Quantization (TSVQ) method which will allow the algori...
متن کاملTexture Synthesis by Fixed Neighborhood Searching a Dissertation Submitted to the Department of Electrical Engineering and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
Textures can describe a wide variety of natural phenomena with random variations over repeating patterns. Examples of textures include images, motions, and surface geometry. Since reproducing the realism of the physical world is a major goal for computer graphics, textures are important for rendering synthetic images and animations. However, because textures are so diverse it is difficult to de...
متن کاملUnsupervised texture classification using vector quantization and deterministic relaxation neural network
This paper describes the use of a neural network architecture for classifying textured images in an unsupervised manner using image-specific constraints. The texture features are extracted by using two-dimensional (2-D) Gabor filters arranged as a set of wavelet bases. The classification model comprises feature quantization, partition, and competition processes. The feature quantization process...
متن کاملFast Image Replacement through Texture Synthesis
We developed a system including two modules: the texture analysis module and the texture synthesis module. The analysis module is capable of analyzing an input image and performing training using this image data. The properties of principal component analysis (PCA) are used to reduce the dimensions of the data representation and to recombine the appearance of the features. Additionally, the vec...
متن کامل