We present a markerless performance capture system that can acquire the motion and the texture of human actors performing fast movements using only commodity hardware. To this end we introduce two novel concepts: First, a staggered surround multi-view recording setup that enables us to perform model-based motion capture on motion-blurred images, and second, a model-based deblurring algorithm wh...

This paper addresses image and signal processing problems where the result most consistent with prior knowledge is the minimum order, or “maximally sparse” solution. These problems arise in such diverse areas as astronomical star image deblurring, neuromagnetic image reconstruction, seismic deconvolution, and thinned array beamformer design. An optimization theoretic formulation for sparse solu...

Motion blur can significantly degrade the quality of an image. The images become blurred due to camera movements, object movements or displacements of pixels. Deblurring of an image is done by processing an image through curvelet transform and removal of noise by median filter. Experimental results show that proposed deblurring technique and accuracy measurement using peak signal to noise ratio...

We present a new approach based on Partial Differential Equations (PDEs) and shock filter theory for deblurring 2D Gaussian blurred images. The inherent problems of stability posed by the reverse heat equation and the discretization of shock filters are overcome by the use of only the initial conditions. This approach is not well suited for diffusion-oriented techniques since in this case the p...

Image deblurring is a relevant problem in many fields of science and engineering. To solve this problem, different approaches have been proposed, and, among the various methods, variational ones are extremely popular. These substitute original with minimization where functional composed two terms, data fidelity term regularization term. In paper we propose, classical non-negative constrained $\...

The images captured in the underwater scene frequently suffer from blur effects due to insufficient light and relative motion between scenes imaging system, which severely hinders visual-based exploration investigation of ocean. In this article, we propose a feature pyramid attention network (FPAN) remove restore blurry images. FPAN incorporates cascaded modules into network, enabling it learn ...