Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  define a distance beten textures for texture classification from texture features based on windod Fourier filters. The definition of the distance relies on an interpretation of our texture attributes in terms of spectral density when the texture can be considered as a Gaussian random field. The distance beten textures is then defined as a symmetrized Kullback distance which is a simple function of the attributes and does not require any normalization. An experimental analysis using Gabor filters, and in particular a comparison to quadratic distances, shows the efficiency and robustness of the method.
['Robert Azencott', 'Jiaping Wang', 'Laurent Younes']
I am writing a research paper on a idea Texture classification using windowed Fourier filters
[{"from": "human", "value": "I am writing a research paper on a idea Texture classification using windowed Fourier filters"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  define a distance beten textures for texture classification from texture features based on windod Fourier filters. The definition of the distance relies on an interpretation of our texture attributes in terms of spectral density when the texture can be considered as a Gaussian random field. The distance beten textures is then defined as a symmetrized Kullback distance which is a simple function of the attributes and does not require any normalization. An experimental analysis using Gabor filters, and in particular a comparison to quadratic distances, shows the efficiency and robustness of the method."}]