Machine learning based hyperspectral image analysis: a survey
Hyperspectral sensors enable the study of the chemical properties of scene materials
remotely for the purpose of identification, detection, and chemical composition analysis of …
remotely for the purpose of identification, detection, and chemical composition analysis of …
Discrete atomic transform-based lossy compression of three-channel remote sensing images with quality control
Lossy compression of remote sensing data has found numerous applications. Several
requirements are usually imposed on methods and algorithms to be used. A large …
requirements are usually imposed on methods and algorithms to be used. A large …
SHyLoC 2.0: A versatile hardware solution for on-board data and hyperspectral image compression on future space missions
In this paper, we present the design, implementation and results of a set of IP cores that
perform on-board hyperspectral image compression according to the CCSDS 123.0-B-1 …
perform on-board hyperspectral image compression according to the CCSDS 123.0-B-1 …
Quality control for the BPG lossy compression of three-channel remote sensing images
This paper deals with providing the desired quality in the Better Portable Graphics (BPG)-
based lossy compression of color and three-channel remote sensing (RS) images. Quality is …
based lossy compression of color and three-channel remote sensing (RS) images. Quality is …
Full-reference quality metric based on neural network to assess the visual quality of remote sensing images
Remote sensing images are subject to different types of degradations. The visual quality of
such images is important because their visual inspection and analysis are still widely used …
such images is important because their visual inspection and analysis are still widely used …
Bpg-based automatic lossy compression of noisy images with the prediction of an optimal operation existence and its parameters
With a resolution improvement, the size of modern remote sensing images increases. This
makes it desirable to compress them, mostly by using lossy compression techniques. Often …
makes it desirable to compress them, mostly by using lossy compression techniques. Often …
Principal component reconstruction error for hyperspectral anomaly detection
JA Jablonski, TJ Bihl, KW Bauer - IEEE Geoscience and …, 2015 - ieeexplore.ieee.org
In this letter, a reliable, simple, and intuitive approach for hyperspectral imagery (HSI)
anomaly detection (AD) is presented. This method, namely, the global iterative principal …
anomaly detection (AD) is presented. This method, namely, the global iterative principal …
BPG-Based lossy compression of three-channel noisy images with prediction of optimal operation existence and its parameters
Nowadays, there is a clear trend toward increasing the number of remote-sensing images
acquired and their average size. This leads to the need to compress the images for storage …
acquired and their average size. This leads to the need to compress the images for storage …
A fast and accurate prediction of distortions in DCT-based lossy image compression
Since the number of acquired images and their size have the tendency to increase, their
lossy compression is widely applied for their storage, transfer, and dissemination …
lossy compression is widely applied for their storage, transfer, and dissemination …
Lossy compression of multichannel remote sensing images with quality control
Lossy compression is widely used to decrease the size of multichannel remote sensing data.
Alongside this positive effect, lossy compression may lead to a negative outcome as making …
Alongside this positive effect, lossy compression may lead to a negative outcome as making …