PROJECT TITLE :

Denoising Of Hyper-spectral Image Using Low-Rank Matrix Factorization - 2017

ABSTRACT:

Restoration of hyperspectral pictures (HSIs) is a difficult task, thanks to the reason that images are inevitably contaminated by a mix of noise, as well as Gaussian noise, impulse noise, dead lines, and stripes, throughout their acquisition method. Recently, HSI denoising approaches primarily based on low-rank matrix approximation became a vigorous research field in remote sensing and have achieved state-of-the-art performance. These approaches, but, unavoidably need to calculate full or partial singular value decomposition of huge matrices, leading to the relatively high computational cost and limiting their flexibility. To address this issue, this letter proposes a methodology exploiting an occasional-rank matrix factorization theme, in that the associated strong principal element analysis is solved by the matrix factorization of the low-rank part. Our methodology desires solely an higher sure of the rank of the underlying low-rank matrix instead of the precise value. The experimental results on the simulated and real data sets demonstrate the performance of our technique by removing the mixed noise and recovering the severely contaminated pictures.


Did you like this research project?

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


PROJECT TITLE : Use of a Tracer-Specific Deep Artificial Neural Net to Denoise Dynamic PET Images ABSTRACT: The use of kinetic modeling (KM) on a voxel level in dynamic PET pictures frequently results in large amounts of noise,
PROJECT TITLE : A Convergent Image Fusion Algorithm Using Scene-Adapted Gaussian-Mixture-Based Denoising ABSTRACT: Inspired by contemporary PnP frameworks, we offer a new picture fusion technique. When a denoiser is used in PnP,
PROJECT TITLE : Statistical Nearest Neighbors for Image Denoising ABSTRACT: Non-local-means image denoising is based on processing a reference patch's neighbours. The algorithm's processing overhead can be reduced by using a small
PROJECT TITLE :External Prior Guided Internal Prior Learning for Real-World Noisy Image Denoising - 2018ABSTRACT:Most of existing image denoising ways learn image priors from either an external data or the noisy image itself
PROJECT TITLE :EEG Signal Denoising based on Wavelet Transform using Xilinx System Generator - 2018ABSTRACT:Low amplitude EEG signal are simply affected by varied noise sources. This work presents de-noising methods based on the

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

Project Enquiry