IEEE Trans Image Process - High-accuracy total variation with application to compressed video sensing.

Tópicos

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Resumo

Numerous total variation (TV) regularizers, engaged in image restoration problem, encode the gradients by means of simple [-1, 1] finite-impulse-response (FIR) filter. Despite its low computational processing, this filter severely distorts signal's high-frequency components pertinent to edge/ discontinuous information and cause several deficiency issues known as texture and geometric loss. This paper addresses this problem by proposing an alternative model to the TV regularization problem via high-order accuracy differential FIR filters to preserve rapid transitions in signal recovery. A numerical encoding scheme is designed to extend the TV model into multidimensional representation (tensorial decomposition). We adopt this design to regulate the spatial and temporal redundancy in compressed video sensing problem to jointly recover frames from undersampled measurements. We then seek the solution via alternating direction methods of multipliers and find a unique solution to quadratic minimization step with capability of handling different boundary conditions. The resulting algorithm uses much lower sampling rate and highly outperforms alternative state-of-the-art methods. This is evaluated both in terms of restoration accuracy and visual quality of the recovered frames.

Resumo Limpo

numer total variat tv regular engag imag restor problem encod gradient mean simpl finiteimpulserespons fir filter despit low comput process filter sever distort signal highfrequ compon pertin edg discontinu inform caus sever defici issu known textur geometr loss paper address problem propos altern model tv regular problem via highord accuraci differenti fir filter preserv rapid transit signal recoveri numer encod scheme design extend tv model multidimension represent tensori decomposit adopt design regul spatial tempor redund compress video sens problem joint recov frame undersampl measur seek solut via altern direct method multipli find uniqu solut quadrat minim step capabl handl differ boundari condit result algorithm use much lower sampl rate high outperform altern stateoftheart method evalu term restor accuraci visual qualiti recov frame

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