Resolving scaling ambiguities with the norm in a blind. Examples of discrete signals used to calculate the varimax norm. Reflections on the deconvolution of land seismic data. Microvolution offers a revolution in 3d deconvolution technology, with speeds up to 200 times faster than the competition.
Modified residual norm steepest descent, wiener filter preconditioned landweber, conjugate gradient for least squares and hybrid bidiagonalization regularization. Resolving scaling ambiguities with the 1 2 norm in a blind deconvolution problem with feedback ernie essery, tim t. Deconvolution of marine seismic data using the l1 norm. Seismic deconvolution using the mixed norm of lp regularization along the time. A novel entropybased equalization performance measure and relations to lp norm deconvolution. The kernel estimate is the key to the blind deconvolution problem, in this paper, we first obtain the intermediate clearer image using the prior based on generalized l p l q norm on image derivatives, then use this estimated. Opendtect software, in the netherlands offshore f3 block. We show that for an exact convolutional forward model and statistically independent. We use cookies to offer you a better experience, personalize content, tailor advertising, provide social media features, and better understand the use of our services. Sparse signal estimation by maximally sparse convex. Chapman, ian barrodale summary the trace measured in a marine seismic experiment can be expressed as the convolution of.
Most prior work eliminates this ambiguity by fixing the l1 norm of the blur kernel. University of toulouse, irit umr cnrs 5505, toulouse, france abstract it has been recently shown that compressive sampling is an interesting perspective for fast ultrasound imaging. Seismic deconvolution using the mixed norm of lp regularization. In sparse signal processing, the l1 norm has special sig nificance 4, 5. Herrmann department of earth, ocean and atmospheric sciences.
No accessseg technical program expanded abstracts 2018. Soot l1l2 norm ratio sparse blind deconvolution file exchange. Ultrasound compressive deconvolution with p norm prior zhouye chen, ningning zhao, adrian basarab, denis kouame. Pdf deconvolution of seismic data using phase change operators. I know them, just dont understand why l1 norm for sparse models.
Chen, zhouye and zhao, ningning and basarab, adrian and kouame, denis ultrasound compressive deconvolution with lp norm prior. Be able to reduce the time required to manage critical changes and repetitive tasks across complex, multivendor networks. Adaptive blind deconvolution using generalized cross. For instance, if we assume sparse and spiky reflectivity and gaussian noise with zero mean, the lp. Soot l1l2 norm ratio sparse blind deconvolution file. Please feel free to ask me any question and report bugs. A matlab program deconvl1 implementing sparse deconvolution using.
Sparse blind deconvolution in gaussian noise with a nonconvex regularized l1l2 norm ratio penalty. One class of alternatives is lpnorm deconvolution, l1 norm deconvolution being the bestknown of this class. Resolving scaling ambiguities with the l1l2 norm in a blind. Index termsmultiobservation blind deconvolution, blind image deblurring. We show that both approaches are only equivalent for the case when the noise is minimized with the l2.