Application Of Edge Detection On Ghost Imaging

Edge detection can obtain the edge information of an object,and has a large application in the fields of machine vision and pattern recognition.The traditional edge detection needs to obtain the image of the object first,and then use the edge detection operator to obtain the edge of the object.The edge detection based on ghost imaging can directly obtain the edge information of the unknown object without obtaining the image of the object.This thesis studies the edge detection methods based on ghost imaging.The main results are the following:Firstly,we propose an efficient edge detection method based on ghost imaging(GI),where a novel variable size Sobel operator whose coefficients are isotropic and sensitive to all directions is first designed,and then the “calculated speckles” are computed by the variable size Sobel operator to keep the number of measurements in the GI system unchanged with the size of variable size Sobel operator.Both experimental and simulation results have demonstrated the feasibility of the proposed edge detection method.Furthermore,compared with the edges obtained by GI based edge detection by using the Sobel operator,the edges acquired by the proposed method are clearer and more continuous even under a severely noisy environment.In particular,when the noise is large in the imaging system,the proposed method can also achieve a complete and clear edge,while the method using Sobel operator cannot.Secondly we propose a new edge detection schemes based on a single-pixel imaging in the frequency domain.We have two schemes.In scheme I,special sinusoidal patterns for the x-direction edge and also y-direction edge of the unknown object are first designed.The frequency spectrum for the edge is then obtained using the the four-step phase-shifting method with the designed sinusoidal patterns in single-pixel imaging system.In schemes II,the frequency spectrum of the unknown object is first obtained,then the frequency spectrum for the edge is obtained by calculations.The resulting edges are finally obtained by the inverse Fourier transform on their frequency spectrums.We have also verified the proposed schemes by experiments and numerical simulations.The results show that the proposed schemes can produce higher quality edges of character and also image objects.Comparing with schemes II,the application of schemes I to high frequency components has greatly improved signal-to-noise ratio of the received data in the bucket detector,resulting in better experimental results.Comparing with the edge detection scheme by speckle-shifting in ghost imaging systems,the proposed schemes I shows an improvement in the signal-to-noise ratio.Since a single-pixel imaging system is used,the proposed schemes are capable of reconstructing edges from indirect measurements.The number of measurements required can be effectively reduced due to the sparsity of natural images in the Fourier domain and the conjugate symmetry of real-valued signals' Fourier spectrum.