Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Scale invariance is a fundamental property of ensembles of natural images [1]. Their non Gaussian properties [15, 16] are less ll understood, but they indicate the existence of a rich statistical structure. In this work  present a detailed study of the marginal statistics of a variable related to the edges in the images. A numerical analysis shows that it exhibits extended self-similarity [3, 4, 5]. This is a scaling property stronger than self-similarity: all its moments can be expressed as a por of any given moment. More interesting, all the exponents can be predicted in terms of a multiplicative log-Poisson process. This is the very same model that was used very recently to predict the correct exponents of the structure functions of turbulent flows [6]. These results allow us to study the underlying multifractal singularities. In particular  find that the most singular structures are one-dimensional: the most singular manifold consists of sharp edges.
['Antonio Turiel', 'Germán Mato', 'Néstor Parga', 'Jean-Pierre Nadal']
I am writing a research paper on a idea Self-similarity Properties of Natural Images
[{"from": "human", "value": "I am writing a research paper on a idea Self-similarity Properties of Natural Images"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Scale invariance is a fundamental property of ensembles of natural images [1]. Their non Gaussian properties [15, 16] are less ll understood, but they indicate the existence of a rich statistical structure. In this work  present a detailed study of the marginal statistics of a variable related to the edges in the images. A numerical analysis shows that it exhibits extended self-similarity [3, 4, 5]. This is a scaling property stronger than self-similarity: all its moments can be expressed as a por of any given moment. More interesting, all the exponents can be predicted in terms of a multiplicative log-Poisson process. This is the very same model that was used very recently to predict the correct exponents of the structure functions of turbulent flows [6]. These results allow us to study the underlying multifractal singularities. In particular  find that the most singular structures are one-dimensional: the most singular manifold consists of sharp edges."}]