In this study we concentrate on qualitative topological analysis of the local behavior of the space of natural images. To this end, we use a space of 3 by 3 high-contrast patches ...
Gunnar Carlsson, Tigran Ishkhanov, Vin de Silva, A...
Sub-image search with high accuracy in natural images still remains a challenging problem. This paper proposes a new feature vector called profile for a keypoint in a bag of visual...
Learning a generative model of natural images is a useful way of extracting features that capture interesting regularities. Previous work on learning such models has focused on me...
This paper describes the preliminary work of image separation between natural and artificial objects using fractal dimensions by noting that most of natural images have non-intege...
The observed distribution of natural images is far from uniform. On the contrary, real images have complex and important structure that can be exploited for image processing, reco...
Abstract This paper presents a segmentation technique based on prediction and adaptive region merging. While many techniques for segmentation exist, few of them are suited for the ...
Visual cortex neurons have receptive fields resembling oriented bandpass filters, and their response distributions on natural images are non-Gaussian. Inspired by this, we previou...
It has been shown that adapting a dictionary of basis functions to the statistics of natural images so as to maximize sparsity in the coefficients results in a set of dictionary ...
This paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in modeling t...
This paper introduces a new method for analyzing scaling phenomena in natural images, and draws some consequences as to whether natural images belong to the space of functions with...