Blind image quality assessment with the histogram sequences of high-order local derivative patterns
Automatic assessment of the perceptual quality of digital image is an important and challenging issue in computer vision. Although human visual system (HVS) is sensitive to degradations on spatial structures, most of the existing methods do not take ...
ALAVIT
It is well-known that the layered transmission for video bit-streams generated by a layered coding can gracefully accommodate the receivers' heterogeneity in wireless networks. In this paper, we propose a new layered video transmission scheme employing ...
A convex hull approach in conjunction with Gaussian mixture model for salient object detection
The capability of humans in distinguishing salient objects from background is at par excellence. The researchers are yet to develop a model that matches the detection accuracy as well as computation time taken by the humans. In this paper we attempted ...
High resolution time-frequency representation for chirp signals using an adaptive system based on duffing oscillators
This paper presents a novel methodology to estimate the frequency shift in chirp signals with SNRs as low as -17 dB through the use of an adaptive array of Duffing oscillators. The system used here is an array of five Duffing oscillators with each ...
Fast convolutional sparse coding using matrix inversion lemma
Convolutional sparse coding is an interesting alternative to standard sparse coding in modeling shift-invariant signals, giving impressive results for example in unsupervised learning of visual features. In state-of-the-art methods, the most time-...
Elimination of end effects in local mean decomposition using spectral coherence and applications for rotating machinery
Local mean decomposition (LMD) is widely used in signal processing and fault diagnosis of rotating machinery as an adaptive signal processing method. It is developed from the popular empirical mode decomposition (EMD). Both of them have an open problem ...
A digital multichannel neural signal processing system using compressed sensing
This paper concerns a wireless multichannel neural recording system using a compressed sensing technique to compress the recorded data. We put forth a single and a multichannel system applying a Minimum Euclidean or Manhattan Distance Cluster-based (MDC)...
Adaptive linear discriminant regression classification for face recognition
Linear discriminant regression classification (LDRC) was presented recently in order to boost the effectiveness of linear regression classification (LRC). LDRC aims to find a subspace for LRC where LRC can achieve a high discrimination for ...
Tackling the flip ambiguity in wireless sensor network localization and beyond
There have been significant advances in range-based numerical methods for sensor network localizations over the past decade. However, there remain a few challenges to be resolved to satisfaction. Those issues include, for example, the flip ambiguity, ...