This paper introduces a texture representation suitable for image synthesis of textured surfaces. An efficient representation for natural images is of fundamental importance in image processing and analysis. The automated analysis of texture is widely applied in a number of real-world
applications, e.g., image and video retrieval, object recognition and classification. For texture representation we consider the orthogonal decomposition of two-dimensional signals (images) using spectral transform in the different basis functions. This paper focuses on the analysis of the
following basis functions Fourier, Walsh, Haar, Hartley and cosine transform using system criteria analysis. This criterion includes error signal representation and computational cost. For correct calculation of the components of the system criterion we use statistical averaging. It is shown
that the Haar transform can represent textural patches more efficiently with smaller average risk than other basis functions. The texture representations results compare favourably against other state-of-the-art directional representations.
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Document Type: Research Article
Publication date: 29 January 2017
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