Subpixel Edge Detection Algorithm for Blurred Image Based on Visual Perception Model
At present,a lot of image information exists in the image edge,and the pixel level in the image edge detection has been unable to fully meet the needs of image information extraction.Therefore,it is necessary to upgrade the pixel unit to the sub-pixel level.In this article,an algorithm for detecting fuzzy image sub-pixel edges was pro-posed based on a visual perception model.Firstly,a fuzzy image restoration model was constructed,and then the frog leaping algorithm was adopted to optimize the fuzzy image.Secondly,the original image was estimated by the maximum likelihood,thus generating a restored image.Based on the synaptic transmission model and the visual per-ception model,a visual perception neuron model was constructed to detect the pixel level of the image edge,and then the B-spline interpolation method was used to obtain an insertion point.Moreover,the image pixel edge was interpola-ted to obtain the image a sub-pixel edge.Finally,the sub-pixel edge detection of fuzzy images was completed.Exper-imental results show that the proposed method has a higher FOM value and obtains more comprehensive image edge information,with more rich details as well as shorter detection time.Therefore,this method can be widely used in the image detection field.
NETL
NSTL
万方数据
