PROJECT TITLE :

No-reference quality assessment for Multiplydistorted images in gradient domain - 2016

ABSTRACT:

In apply, pictures on the market to customers sometimes bear many stages of processing including acquisition, compression, transmission, and presentation, and each stage may introduce bound type of distortion. It's common that images are simultaneously distorted by multiple sorts of distortions. Most existing objective image quality assessment (IQA) strategies have been designed to estimate perceived quality of images corrupted by one image processing stage. During this letter, we propose a no-reference (NR) IQA technique to predict the visual quality of multiply-distorted images primarily based on structural degradation. Within the proposed methodology, a novel structural feature is extracted as the gradient-weighted histogram of local binary pattern (LBP) calculated on the gradient map (GWH-GLBP), which is effective to describe the advanced degradation pattern introduced by multiple distortions. In depth experiments conducted on two public multiply-distorted image databases have demonstrated that the proposed GWH-GLBP metric compares favorably with existing full-reference and NR IQA ways in terms of high accordance with human subjective ratings.


Did you like this research project?

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


PROJECT TITLE :NIQSV+ A No-Reference Synthesized View Quality Assessment Metric - 2018ABSTRACT:Benefiting from multi-read video and depth and depth-image-based mostly-rendering technologies, only limited views of a real 3-D scene
PROJECT TITLE : Towards a no-reference image quality assessment Using statistics of perceptual color descriptors - 2016 ABSTRACT: Analysis of the statistical properties of natural images has played a important role in the design
PROJECT TITLE : Binocular responses for no-reference 3d image Quality assessment - 2016 ABSTRACT: Perceptual quality assessment of distorted three-dimensional (3D) images has become a basic nevertheless challenging issue in
PROJECT TITLE : No-Reference Image Sharpness Assessment in Autoregressive Parameter Space - 2015 ABSTRACT: During this paper, we propose a brand new no-reference (NR)/ blind sharpness metric in the autoregressive (AR) parameter
PROJECT TITLE : Video Dissemination over Hybrid Cellular and Ad Hoc Networks - 2014 ABSTRACT: We study the problem of disseminating videos to mobile users by using a hybrid cellular and ad hoc network. In particular, we formulate

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

Project Enquiry