A model for image patch-based algorithms

An empirical study of the domain of patch-based learning algorithms for image and video processing is conducted. As patch-based algorithms are commonly used, knowledge of the properties of xed size image patches would prove particularly useful and interesting. We are concerned with investigating the overall distribution of vectorized patches of general images. A multivariate distribution model is proposed and analyzed using various techniques, which include univariate histograms and modi ed k-nearest neighbors. The model is veri ed and an application using the distribution model is introduced and compared.

• Type: Conference
• Year: 2008
• Where: ICIP
• Authors: Karl S. Ni, Truong Q. Nguyen
• Keywords: ICIP 2008, Image Processing, K-nearest Neighbors, Multivariate Distribution Model, Patch-based Learning Algorithms, Size Image Patches, Vectorized Patches