PROJECT TITLE :

Bayesian Structure-Preserving Image Contrast Enhancement and its Simplification

ABSTRACT:

During this paper, an economical Bayesian framework is proposed for image contrast enhancement. Primarily based on the image acquisition pipeline, we tend to model the image enhancement downside as a maximum a posteriori (MAP) estimation downside, where the posteriori likelihood is formulated based on the native data of the given image. In our framework, we tend to categorical the probability model as a native image structure preserving constraint, where the overall effect of the shutter speed and camera response perform is approximated as a linear transformation. On the opposite hand, we style the prior model primarily based on the observed image and some statistical property of natural pictures. With the proposed framework, we have a tendency to can effectively enhance the contrast of the image in an exceedingly natural-trying method, whereas with fewer artifacts at the identical time. Moreover, so as to apply the proposed MAP formulation to typical enhancement issues, like image editing, we tend to more convert the estimation method into an intensity mapping method, which will achieve comparable enhancement performance with a abundant lower computational complexity. Simulation results have demonstrated the feasibility of the proposed framework in providing versatile and effective distinction enhancement.


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 :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 :Fast Low-Rank Bayesian Matrix Completion With Hierarchical Gaussian Prior Models - 2018ABSTRACT:The problem of low-rank matrix completion is taken into account in this Project. To use the underlying low-rank structure
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
PROJECT TITLE :An Asymmetric Evolutionary Bayesian Coalition Formation Game for Distributed Resource Sharing in a Multi-Cell Device-to-Device Enabled Cellular Network - 2018ABSTRACT:We have a tendency to present a unique game,

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

Project Enquiry