We present a deep-learning approach to restore sequence of turbulence-distorted video frames from turbulent deformations and space-time varying blurs. Instead requiring massive training sample size in deep networks, we purpose strategy that is based on new data augmentation method model turbulence relatively small dataset. Then introduce subsampled enhance the restoration performance presented ...

The conventional TCP tends to suffer from performance degradation due to packet corruptions in the wireless lossy channels, since any corruption event is regarded as an indication of network congestion. This paper proposes a TCP error and congestion control scheme using corruption-aware adaptive increase and adaptive decrease algorithm to improve TCP performance over wireless networks. In the p...

A new method for correction of MRI motion artifacts induced by corrupted k-space data, acquired by multiple receiver coils such as phased arrays, is presented. In our approach, a projections onto convex sets (POCS)-based method for reconstruction of sensitivity encoded MRI data (POCSENSE) is employed to identify corrupted k-space samples. After the erroneous data are discarded from the dataset,...

Digital image processing plays important role in our daily life. Digital Image Processing involves the modification of digital data for improving the image qualities with the aid of computer. The processing helps in maximize the clarity, sharpness of image and details of features of interest. The digital image is given as input into a computer and computer is programmed to change data with the ...

For entropy-coded H.264/AVC video frames, a transmission error in a codeword will not only affect the underlying codeword but also may affect subsequent codewords, resulting in a great degradation of the received video frames. In this study, an error resilient coding scheme for H.264/AVC video transmission is proposed. At the encoder, for an H.264/AVC intra-coded I frame, the important data for...

Our work relies on the design and evaluation of experimental information retrieval systems able to cope with textual misspellings in queries. In contrast to previous proposals, commonly based on the consideration of spelling correction strategies and a word language model, we also report on the use of character n-grams as indexing support.

We proposed a weighted l minimization: min , ‖x‖ + λ‖f‖ s.t.Ax+ f= b to recover a sparse vector x and the corrupted noise vector f from a linear measurement b = Ax + f when the sensing matrix A is an m × n row i.i.d subgaussian matrix. Our first result shows that the recovery is possible when the fraction of corrupted noise is smaller than a positive constant, provided that ‖x‖ ≤ O(n/ln (n/‖x ∗...

For deblurring images corrupted by random valued noise, two-phase methods first select likely-to-be reliables (data that are not corrupted by random valued noise) and then deblur images only with selected data. The selective use of data in twophase methods, however, often causes missing data artifacts. In this paper, to suppress these missing data artifacts, we propose a blurring model based re...

Subsampling methods have been recently proposed to speed up least squares estimation in large scale settings. However, these algorithms are typically not robust to outliers or corruptions in the observed covariates. The concept of influence that was developed for regression diagnostics can be used to detect such corrupted observations as shown in this paper. This property of influence – for whi...