Depth Restoration From RGB-D Data via Joint Adaptive Regularization and Thresholding on Manifolds


By integrating the properties of local and non-local manifolds that offer low-dimensional parameterizations of local and non-local geometry of depth maps, we have developed a novel depth restoration algorithm using RGB-D data. Manifold regularisation is presented to enhance smoothing along the manifold structure by first defining a local manifold model that favours local nearby relationships of pixels in depth. It is also possible to exploit the patch-based manifold's non-local properties, such as its self-similar structures, to develop highly data-adaptive orthogonal bases to extract extended visual patterns. A manifold thresholding operator in 3D adaptive orthogonal spectral bases (eigenvectors of the discrete Laplacian of local and non-local manifolds) is further defined to keep only low graph frequencies for depth map restoration. Lastly, we present an efficient alternating direction approach of multipliers optimization framework that combines adaptive manifold regularisation and thresholding to solve the inverse problem of depth map recovery... Our strategy outperforms the current state-of-the-art in both objective and subjective quality evaluations, according to the findings of experiments.

Did you like this research project?

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

PROJECT TITLE : CANet Cross-Disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading ABSTRACT: One in three people who are working-age and have diabetes will go blind due to diabetic retinopathy
PROJECT TITLE : Depth Super-Resolution via Joint Color-Guided Internal and External Regularizations ABSTRACT: Many real-world applications make heavy use of depth information. In practise, however, depth maps tend to have a lower
PROJECT TITLE : Graph-based Joint Dequantization and Contrast Enhancement of Poorly Lit JPEG Images ABSTRACT: The lossy compression of JPEG images results in images with low contrast and coarse quantization artefacts in low-light
PROJECT TITLE : Graph-Regularized Locality-Constrained Joint Dictionary and Residual Learning for Face Sketch Synthesis ABSTRACT: For digital entertainment and police enforcement, face sketch synthesis is a critical issue It's
PROJECT TITLE : Image Co-Saliency Detection and Co-Segmentation via Progressive Joint Optimization ABSTRACT: New computational models for simultaneous picture co-saliency detection and co-segmentation are presented here that simultaneously

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

Project Enquiry