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8 January 2008 A robust sub-pixel edge detection method of infrared image based on tremor-based retinal receptive field model
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Abstract
Because of complex thermal objects in an infrared image, the prevalent image edge detection operators are often suitable for a certain scene and extract too wide edges sometimes. From a biological point of view, the image edge detection operators work reliably when assuming a convolution-based receptive field architecture. A DoG (Difference-of- Gaussians) model filter based on ON-center retinal ganglion cell receptive field architecture with artificial eye tremors introduced is proposed for the image contour detection. Aiming at the blurred edges of an infrared image, the subsequent orthogonal polynomial interpolation and sub-pixel level edge detection in rough edge pixel neighborhood is adopted to locate the foregoing rough edges in sub-pixel level. Numerical simulations show that this method can locate the target edge accurately and robustly.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kun Gao, Hu Yang, Xiaomei Chen, and Guoqiang Ni "A robust sub-pixel edge detection method of infrared image based on tremor-based retinal receptive field model", Proc. SPIE 6835, Infrared Materials, Devices, and Applications, 68351Y (8 January 2008); https://doi.org/10.1117/12.758162
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