An approach to prediction and providing of compression ratio for DCT based coder applied to remote sensing images

An approach to prediction and providing of compression ratio for DCT based coder applied to remote sensing images

Gespeichert in:

Bibliographische Detailangaben
Datum:	2016
Hauptverfasser:	R. A. Kozhemiakin, A. N. Zemliachenko, V. V. Lukin, S. K. Abramov, B. Vozel
Format:	Artikel
Sprache:	English
Veröffentlicht:	2016
Schriftenreihe:	Ukrainian journal of remote sensing
Online Zugang:	http://jnas.nbuv.gov.ua/article/UJRN-0000533654
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!
Назва журналу:	Library portal of National Academy of Sciences of Ukraine \| LibNAS

Institution

Library portal of National Academy of Sciences of Ukraine | LibNAS

Ähnliche Einträge

An approach to prediction and providing of compression ratio for DCT based coder applied to remote sensing images
von: Kozhemiakin, Ruslan, et al.
Veröffentlicht: (2016)

Usage of different Chroma Subsampling Modes in Image Compression by BPG Coder
von: Kovalenko, Bogdan, et al.
Veröffentlicht: (2022)

Usage of different Chroma Subsampling Modes in Image Compression by BPG Coder
von: B. V. Kovalenko, et al.
Veröffentlicht: (2022)

APPROACHES TO PREDICTION OF SPECKLE REMOVAL EFFICIENCY FOR DCT-BASED FILTER
von: Lukin, V. V., et al.
Veröffentlicht: (2015)

Approaches to prediction of speckle removal efficiency for DCT-based filter
von: V. V. Lukin, et al.
Veröffentlicht: (2014)

Strange Images in Remote Sensing and Their Properties
von: Li, Fangfang, et al.
Veröffentlicht: (2023)

Strange images in remote sensing and their properties
von: F. Li, et al.
Veröffentlicht: (2023)

Prediction of Parameters in Optimal Operation Point for BPG-based Lossy Compression of Noisy Images
von: Kovalenko, Bogdan, et al.
Veröffentlicht: (2022)

Prediction of Parameters in Optimal Operation Point for BPG-based Lossy Compression of Noisy Images
von: B. V. Kovalenko, et al.
Veröffentlicht: (2022)

Neural and statistical techniques for remote sensing image classification
von: Grypych, Iu., et al.
Veröffentlicht: (2010)

Remote sensing of snowfalls. Review
von: A. B. Veselovskaja
Veröffentlicht: (2015)

Method of features construction for remote sensing images based on the characteristics of random point fields
von: Ya. Kosarevych, et al.
Veröffentlicht: (2017)

Coder and decoder of fractal signals of comb-type structure
von: R. L. Politanskij, et al.
Veröffentlicht: (2014)

Classification of BPG-Based Lossy Compressed Noisy Images
von: Proskura, Galina, et al.
Veröffentlicht: (2024)

Analysis of remote sensing images by methods of convolutional neural networks and marked random point fields
von: Ya. Kosarevych, et al.
Veröffentlicht: (2021)

Predictive assessment for the potential pollution of underground hydrosphere due to extraction of unconventional hydrocarbons (using remote sensing data)
von: V. I. Lialko, et al.
Veröffentlicht: (2017)

Predictive assessment for the potential pollution of underground hydrosphere due to extraction of unconventional hydrocarbons (using remote sensing data)
von: Lyalko, Vadim, et al.
Veröffentlicht: (2017)

Remote sensing from space in investment prospect
von: Yu. V. Bukhun
Veröffentlicht: (2015)

Three-frequency remote sensing of liquid precipitation
von: A. M. Linkova, et al.
Veröffentlicht: (2016)

On the development of remote sensing methods and technologies in Ukraine
von: Lyalko, Vadim, et al.
Veröffentlicht: (2022)

On The Development Of Remote Sensing Methods And Technologies In Ukraine
von: V. I. Lialko, et al.
Veröffentlicht: (2022)

A novel approach to remote sensing of vegetation
von: Bidyuk, P.I., et al.
Veröffentlicht: (2005)

THE USE OF REMOTE SENSING AND GEOLOGICAL AND GEOPHYSICAL DATA FOR PREDICT OF THE SPREAD OF DNIEPER BASIN BUCHAK’S LIGNITE DEPOSITS ON THE BASIS OF NEOTECTONIC ANALYSIS
von: Пазинич, Н. В., et al.
Veröffentlicht: (2015)

Analysis of the potential efficiency of post-filtering noisy images after lossy compression
von: Kovalenko, Bogdan, et al.
Veröffentlicht: (2023)

Determination of self-foresting areas by remote sensing data
von: Horelyk, Stanislav, et al.
Veröffentlicht: (2024)

Control System for Meteorological Complex of Atmosphere Remote Sensing
von: Vavriv, D. M., et al.
Veröffentlicht: (2013)

The use of remote sensing and geological and geophysical data for predict of the spread of Dniper basin Buchak's lignite deposits on the basis of neotectonic analysis
von: N. V. Pazynych, et al.
Veröffentlicht: (2015)

Analysis of the potential efficiency of post-filtering noisy images after lossy compression
von: B. V. Kovalenko, et al.
Veröffentlicht: (2023)

Application of filtering efficiency prediction to hyperspectral data pre-processing
von: V. V. Lukin, et al.
Veröffentlicht: (2015)

APPLICATION OF FILTERING EFFICIENCY PREDICTION TO HYPERSPECTRAL DATA PRE-PROCESSING
von: Lukin, V. V., et al.
Veröffentlicht: (2015)

Thermal remote sensing data analysis in monitoring of natural objects
von: O. V. Alokhina, et al.
Veröffentlicht: (2020)

New Method of Engineering Evaluation of Spacecraft for Earth Remote Sensing
von: V. T. Marchenko, et al.
Veröffentlicht: (2017)

Algorithm to assess the technical level of Earth remote sensing spacecraft
von: V. T. Marchenko, et al.
Veröffentlicht: (2017)

On the technology of creation of new technologies in the area of remote sensing of the Earth
von: M. A. Popov
Veröffentlicht: (2018)

Application of Remote Sensing Data for Overall Assessment of Region Soils
von: L. V. Hebryn, et al.
Veröffentlicht: (2015)

Remote sensing of the Earth Using the method of structural-tectonic Analysis
von: R. V. Shulha
Veröffentlicht: (2015)

On the technology of creation of new technologies in the area of remote sensing of the Earth
von: Popov, Mykhailo
Veröffentlicht: (2018)

Utilizing remotely sensed data for atmospheric precipitation analysis in Ukraine
von: Аpostolov, Aleksandr, et al.
Veröffentlicht: (2024)

Novel Remote Sensing Methods for Minerals Prospecting. Chapter 1
von: CASRE, SI
Veröffentlicht: (2017)

Multipurpose Airborne Earth's Remote Sensing Radar System “MARS”
von: Kalmykov, A. I., et al.
Veröffentlicht: (2013)