PROJECT TITLE :

A Variational Pansharpening Approach Based on Reproducible Kernel Hilbert Space and Heaviside Function - 2018

ABSTRACT:

Pansharpening is a vital application in remote sensing Image Processing. It will increase the spatial-resolution of a multispectral image by fusing it with a high spatial-resolution panchromatic image in the identical scene, that brings great favor for subsequent processing like recognition, detection, etc. During this Project, we propose endless modeling and sparse optimization based mostly method for the fusion of a panchromatic image and a multispectral image. The proposed model is mainly primarily based on reproducing kernel Hilbert space (RKHS) and approximated Heaviside function (AHF). Further, we additionally propose a Toeplitz sparse term for representing the correlation of adjacent bands. The model is convex and solved by the alternating direction methodology of multipliers that guarantees the convergence of the proposed method. Intensive experiments on many real datasets collected by totally different sensors demonstrate the effectiveness of the proposed technique as compared with many state-of-the-art pansharpening approaches.


Did you like this research project?

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


PROJECT TITLE : A Novel Retinex-Based Fractional-Order Variational Model for Images With Severely Low Light ABSTRACT: A new fractional-order variational model based on Retinex is proposed in this research for low-light photos.
PROJECT TITLE : Variational Bayesian Blind Color Deconvolution of Histopathological Images ABSTRACT: In most whole-slide histology images, two or more chemical dyes are used. In digital pathology, slide stain separation or colour
PROJECT TITLE : Variational Osmosis for Non-Linear Image Fusion ABSTRACT: Non-linear image fusion can be improved by using a novel variational model proposed by us. Osmosis energy terms that are similar to those explored in Vogel
PROJECT TITLE : A Robust Group-Sparse Representation Variational Method With Applications to Face Recognition ABSTRACT: For face recognition applications, we offer a Group-Sparse Representation-based technique (GSR-FR). A non-convex
PROJECT TITLE : Structure-Texture Image Decomposition Using Deep Variational Priors ABSTRACT: Structure-texture image decomposition invariably requires structure pictures to have modest norms in some functional spaces and to share

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

Project Enquiry