Search
2 articles for “MSI denoising”
-
Multispectral Image Denoising using Bi-Directional Recurrent Neural Network with DPCA Algorithm
Abstract: In practices, a Multispectral Images (MSI) image is always prone to corruption by various sources of noises while procuring the images. In this paper we implemented Decomposable Pixel Component Analysis (DPCA) algorithm with recurrent neural network (RNN) which effectively denoised the MSI images. The RNN enables shrinkage of non-reusable data points during DPCA execution and aid it to effectively transform spatial coordinate in a logical manner and reduces the time …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 25–30 Read article
-
A Novel Decomposable Pixel Component Analysis Algorithm for Automating Multispectral Satellite Image Denoising
Abstract: In comparison with the standard RGB or gray-scale images the usual multispectral images (MSI) is intended to convey high definition and an authentic representation for real world scenes to significantly enhance the performance measures of several other tasks involving with computer vision, segmentation of image, object extraction and object tagging operations. However, in practices a MSI image is always prone to corruption by various sources of noises while procuring the …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 2, Issue 3, 2014 · pp. 18–25 Read article