Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a new operator called shape operator for describing image structure.  consider an image function as a surface, then describe a shape of each pixel comparing with its neighbourhood in terms of topographical shapes such as hill, dale, ridge, valley, etc. The shape operator is established by utilizing the eigenvalues of Hessian of an image function.  show how to derive this operator, and its interesting properties. Finally,  illustrate by examples how the shape operator can give the same interpretation of an image although the image is corrupted by shading effects, and how it can give the same interpretation of an image vied in different viewpoints.
['Phongsuphap Sukanya', 'R. Takamatsu', 'I. Sato']
I am writing a research paper on a idea A new operator for image structure analysis
[{"from": "human", "value": "I am writing a research paper on a idea A new operator for image structure analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a new operator called shape operator for describing image structure.  consider an image function as a surface, then describe a shape of each pixel comparing with its neighbourhood in terms of topographical shapes such as hill, dale, ridge, valley, etc. The shape operator is established by utilizing the eigenvalues of Hessian of an image function.  show how to derive this operator, and its interesting properties. Finally,  illustrate by examples how the shape operator can give the same interpretation of an image although the image is corrupted by shading effects, and how it can give the same interpretation of an image vied in different viewpoints."}]