Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the recent years, denoising based on the spatially adaptive algorithms that employ anisotropic adaption have been developed. These methods are able to match to the local statistics, preserve the edges and truly remove the noise from the texture of the images. On the other hand, a huge proportion of image enhancement methods are implemented in the sparse domains (e.g., wavelets, curvelets, contourlets and steerable pyramid decomposition) due to impressive properties of these transforms such as heavy-tailed nature of marginal distribution, locality and multiresolution.   try to establish a relation beten two mentioned approaches by estimating the local variances of steerable pyramid coefficients using a shape-adaptive window.
['Hossein Rabbani']
I am writing a research paper on a idea Shape adaptive estimation of variance in steerable pyramid domain and its application for spatially adaptive image enhancement
[{"from": "human", "value": "I am writing a research paper on a idea Shape adaptive estimation of variance in steerable pyramid domain and its application for spatially adaptive image enhancement"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the recent years, denoising based on the spatially adaptive algorithms that employ anisotropic adaption have been developed. These methods are able to match to the local statistics, preserve the edges and truly remove the noise from the texture of the images. On the other hand, a huge proportion of image enhancement methods are implemented in the sparse domains (e.g., wavelets, curvelets, contourlets and steerable pyramid decomposition) due to impressive properties of these transforms such as heavy-tailed nature of marginal distribution, locality and multiresolution.   try to establish a relation beten two mentioned approaches by estimating the local variances of steerable pyramid coefficients using a shape-adaptive window."}]