PROJECT TITLE :

Compressive Video Sampling With Approximate Message Passing Decoding

ABSTRACT:

In this paper, we apply compressed sensing (CS) to video compression. CS techniques exploit the observation that one wants abundant fewer random measurements than given by the Shannon–Nyquist sampling theory to recover an object if this object is compressible (i.e., sparse in the spatial domain or in a very remodel domain). Within the CS framework, we will achieve sensing, compression, and denoising simultaneously. We propose a quick and easy on-line encoding by the appliance of pseudorandom downsampling of the two-D fast Fourier transform to video frames. For offline decoding, we have a tendency to apply a modification of the recently proposed approximate message passing (AMP) algorithm. The AMP methodology has been derived using the statistical concept of “state evolution,” and it's been shown to considerably accelerate the convergence rate in special CS-decoding applications. We have a tendency to shall prove that the AMP technique will be rewritten as a forward–backward splitting algorithm. This new illustration permits us to provide conditions that guarantee convergence of the AMP technique and to change the algorithm so as to achieve higher robustness. The success of reconstruction ways for video decoding conjointly essentially depends on the chosen transform, where sparsity of the video signals is assumed. We propose incorporating the 3-D dual-tree complicated wavelet remodel that possesses sufficiently smart directional selectivity while being computationally less expensive and less redundant than different directional three-D wavelet transforms.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE :Structure-Aware Bayesian Compressive Sensing for Frequency-Hopping Spectrum Estimation With Missing Observations - 2018ABSTRACT:During this Project, we tend to address the matter of spectrum estimation of multiple
PROJECT TITLE :Efficient Compressive Channel Estimation for Millimeter-Wave Large-Scale Antenna Systems - 2018ABSTRACT:Giant-scale antenna systems are thought of as a viable technology to catch up on huge path loss in millimeter-wave
PROJECT TITLE :Frequency-Domain Compressive Channel Estimation for Frequency-Selective Hybrid Millimeter Wave MIMO Systems - 2018ABSTRACT:Channel estimation is helpful in millimeter wave (mm-wave) MIMO communication systems. Channel
PROJECT TITLE :Compressive Channel Estimation and Multi-User Detection in C-RAN With Low-Complexity Methods - 2018ABSTRACT:This Project considers the channel estimation (CE) and multi-user detection (MUD) problems in cloud radio
PROJECT TITLE :Compressive Representation for Device-Free Activity Recognition with Passive RFID Signal Strength - 2018ABSTRACT:Understanding and recognizing human activities could be a basic research topic for a big selection

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry