Reconstruction of the lost phase information in the complex optical field from a single-intensity measurement in the Fourier domain is often termed as phase retrieval. This method can be used in many fields, such as electron microscopy, wavefront sensing, astronomy and crystallography and so on. The classical phase retrieval methods use the two-intensity measurements recorded or single-intensity measurement recorded with some prior knowledge, which utilizes the Gerchberg-Saxton(GS)-like algorithm to iteratively recover the phase of the complex optical field. Aiming at the problem that the single-intensity phase retrieval method has poor reconstruction quality and low probability of successful recovery in practical application, an improved method is proposed in this paper—two-step phase retrieval algorithm from single-exposure measurement. Our proposed method divides the phase retrieval into two steps: first, the GS algorithm combined with prior knowledge is used to recover the amplitude information in the spatial domain from the single-spread Fourier spectrum, and then the classical GS algorithm using two-intensity measurements (one is recorded and the other is estimated from the first step) is used to recover the phase information of the complex optical field behind the coded aperture. Finally, the effectiveness of the proposed method is verified by numerical experiments. Compared with the single-intensity phase retrieval method, our proposed method can significantly improve the reconstruction quality and probability of successful recovery.
In this paper, a novel phase retrieval algorithm is presented which combines the advantages of the Transport of Intensity Equation (TIE) method and the iteration method. TIE method is fast, but its precision is not high. Though the convergence rate of iteration method is slow, its result is more accurate. This algorithm consists of Iterative Angular Spectrum (IAS) method to utilize the physical constraints between the object and the spectral domain, and the relationship between the intensity and phase among the wave propagation. Firstly, the phase at the object plane is calculated from two intensity images by TIE. Then this result is treated as the initial phase of the IAS. Finally, the phase information at the object plane is acquired according the reversibility of the optical path. During the iteration process, the feedback mechanism is imposed on it that improve the convergence rate and the precision of phase retrieval and the simulation results are given.
In classical compressive holography (CH), which based on the Gabor holography setup, two nonlinear terms are inherent in the intensity recorded by a 2D detector arrays, the DC term and the squared field term. The DC term (the term at the origin) can be eliminated by filtering the Fourier transform of the interference irradiance measurements using appropriate high-pass filter near the zero frequency. The nonlinearity caused by the squared field term can be neglected and modeled as a error term in the measurement. However, the above assumptions are significantly limited, which yields the degradation of reconstruction quality. In this paper, an novel scheme using phase-shifting method is presented. To accurately recover the complex optical field caused by the propagation of the object, without the influence of the DC term and the squared field term, a very effective method for removing these two terms is introduced. The complex optical field of the 3D object and the complex optical field at the detector plane can be precisely represented by a linear mapping model. The complex optical field at the recorder plane is obtained by phase-shifting interferometry with multiple shots. Then, the corresponded complex optical field at the detector plane can be successfully extracted from multiple captured holograms using conventional four phase-shifting interferometry. From such complex optical field at the record plane, including the amplitude and phase information, the complex optical field of the 3D object can be reconstructed via an optimization procedure. Numerical results demonstrate the effectiveness of our proposed method.
Depth information of the image is really necessary information to reconstruct a 3-dimensional object.
The classical methods of depth estimation are generally divided into two categories: active and passive
methods. The active methods requires the additional lighting equipment, passive methods also have a
series of problems .They require a plurality of images obtained by capturing a plurality of viewpoints ,
and determine the locating occlusion boundary , etc., and hence the depth estimation has been a
challenging problem in the research field of computer vision.1 Because of the depth information of the
image has a natural sparse features, this paper uses a passive approach, the signal of sparse priori based
on compressed sensing theory is used to estimate the depth of the image, without capturing multiple
images, using a single input image can obtain a high quality depth map. Experimental results show that
the depth map obtaining by our method, compared to the classical passive method, the contour
sharpness, the depth of detail information and the robustness of noise are more advantages. The method
also can be applied to re-focus the defocused images, and automatic scene segmentation and other
issues, ultimately may have broad application prospects in the reconstruction of true 3-dimensional