Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Multispectral imaging system maps the contents of a scene to different intensity levels with in spectral images. This imaging process induces spectral variations among the different wavelength band images of the same scene and results in uncorrelated interest region descrip- tors for cross spectral image matching.  presents Local Binary Pattern of Gradients (LBPG) to improve the strength of interest region description under such spectral variations. In LBPG the image gradients are first transformed into binary patterns and then the gradient pat- terns are used instead of raw gradients for interest region description.  validate the LBPG approach on the spectral images of six different indoor and outdoor scenes. The experimental results confirm better cross spectral image matching performance as compared to SIFT and Center Symmetric Local Binary Patterns.
['Sajid Saleem', 'Robert Sablatnig']
I am writing a research paper on a idea Interest Region Description Using Local Binary Pattern of Gradients
[{"from": "human", "value": "I am writing a research paper on a idea Interest Region Description Using Local Binary Pattern of Gradients"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Multispectral imaging system maps the contents of a scene to different intensity levels with in spectral images. This imaging process induces spectral variations among the different wavelength band images of the same scene and results in uncorrelated interest region descrip- tors for cross spectral image matching.  presents Local Binary Pattern of Gradients (LBPG) to improve the strength of interest region description under such spectral variations. In LBPG the image gradients are first transformed into binary patterns and then the gradient pat- terns are used instead of raw gradients for interest region description.  validate the LBPG approach on the spectral images of six different indoor and outdoor scenes. The experimental results confirm better cross spectral image matching performance as compared to SIFT and Center Symmetric Local Binary Patterns."}]