PROJECT TITLE :

Learning joint demosaicing and denoising based on Sequential energy minimization - 2016

ABSTRACT:

Demosaicing is a crucial first step for color image acquisition. For sensible reasons, demosaicing algorithms must be each efficient and yield high quality ends up in the presence of noise. The demosaicing downside poses several challenges, e.g. zippering and false color artifacts along with edge blur. In this work, we have a tendency to introduce a completely unique learning primarily based methodology that may overcome these challenges. We tend to formulate demosaicing as a picture restoration downside and propose to be told economical regularization galvanized by a variational energy minimization framework that may be trained for various sensor layouts. Our algorithm performs joint demosaicing and denoising in close relation to the $64000 physical mosaicing process on a camera sensor. This can be achieved by learning a sequence of energy minimization problems composed of a group of RGB filters and corresponding activation functions. We evaluate our algorithm on the Microsoft Demosaicing data set in terms of peak signal to noise ratio (PSNR) and structured similarity index (SSIM). Our algorithm is highly efficient both in image quality and run time. We tend to achieve an improvement of up to two.six dB over recent state-of-the-art algorithms.


Did you like this research project?

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


MTechProjects.com offering final year Python Based Machine Learning MTech Projects, Machine Learning IEEE Projects, IEEE Machine Learning Projects, Machine Learning MS Projects, Python Based Machine Learning BTech Projects, Machine
PROJECT TITLE :A Machine Learning Approach for Tracking and Predicting Student Performance in Degree Programs - 2018ABSTRACT:Accurately predicting students' future performance based on their ongoing academic records is crucial
PROJECT TITLE :Optimal Bayesian Transfer Learning - 2018ABSTRACT:Transfer learning has recently attracted important research attention, because it simultaneously learns from different supply domains, that have plenty of labeled
PROJECT TITLE :Learning Graphs With Monotone Topology Properties and Multiple Connected Components - 2018ABSTRACT:Recent papers have formulated the problem of learning graphs from information as an inverse covariance estimation
PROJECT TITLE :Alternative to Extended Block Sparse Bayesian Learning and Its Relation to Pattern-Coupled Sparse Bayesian Learning - 2018ABSTRACT:We tend to consider the matter of recovering block sparse signals with unknown block

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

Project Enquiry