A target position can be estimated using position information from scattered signals in the nonline-of-sight propagation environment in a single observer location system. There is always an error in the final estimated result of the position obtained using scatter signals because measurement noise is inevitable. To reduce the total error of the system, we propose a method of converting the problem of optimizing location into a one of solving the extremes of the constraints. And the problem of how to solve the extremes of the constraints is converted into an unconstrained problem by using the constrained total least squares (CTLS) method. Finally, the Newton iteration method is used to obtain the optimized solution. Simulation results also verify the capability of this method.

Salt and pepper noise occurs randomly and causes image degradation. Numerous denoising methods have been proposed to suppress this noise. However, existing methods have two main limitations. First, noise characteristics, such as noise location information and sparsity, are often described inaccurately or even ignored. Second, many existing methods separate the contaminated image into a recovered image and a noise part, leading to the recovery of an image with unsatisfactory smooth and detailed parts. In this study, the authors introduce a noise detection strategy to determine the position of the noise and employ a non-convex sparsity regularization depicted by l p quasi-norm to describe the sparsity of the noise, thereby addressing the first limitation. We adopt the morphological component analysis framework with stationary Framelet transform to decompose the processed image into the cartoon, texture, and noise parts to resolve the second limitation. Then, the proposed model is applied by using the alternating direction method of multipliers (ADMM). Finally, experiments are conducted to verify the proposed method and compare it with some current state-of-the-art denoising methods. The experimental results show that the proposed method can remove salt and pepper noise while preserving the details of the processed image and outperforming some state-of-the-art methods.

Multiwavelet transform is a new development to the wavelet theory. It can offer orthogonality, symmetry, and short support simultaneously, and can offer a more precise way for image analysis than wavelet multi-resolution. A new remote-sensing image fusion method based on intensity-hue-saturation transform(IHST) and Multiwavelet Transform(MWT) is presented to fusion a multi-spectral image and a panchromatic image. Firstly, the multi-spectral image is transformed with IHST; Secondly, the panchromatic image and I component of the multi-spectral image are merged with MWT-based fusion method, and I component is replaced with the merged data; finally, the fused image is obtained by inverse IHST.Comparing with other methods, the new method can enhance spatial detail information of remote-sensing images largely and provide more spatial information at the same time.

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We theoretically investigated the properties of tightly focused ring Pearcey beams with a cross phase (CPRPB). The expressions of the distributions of both electric field and magnetic field in the focal region of an objective were first derived from the vectorial Debye theory, and then numerical calculations were carried out to obtain the focused intensity distribution and the Poynting vector of CPRPB near the focus. Numerical calculations indicate that as CPRPB is focused on an objective of high numerical aperture (NA), two nonuniform self-focusing spots occur at both sides of the geometrical focus of the objective symmetrically, and the angle between their directions is 90 degrees. The stronger is the strength of cross-phase modulation, the flatter are the ellipses of the self-focusing spots, and the smaller is the intensity at the geometrical focus of the objective. Numerical calculations also demonstrate that the optical gradient force produced by tightly focused CPRPB in the focal region can be manipulated in magnitude and in direction by tuning the strength of cross-phase modulation. Due to these properties of tightly focused CPRPB, they might find applications in the manipulation of micro- and nanoparticles and so on.