Peculiarities of 3D compression of noisy multichannel images

Kozhemiakin, Ruslan; Abramov, Sergey; Djurović, Igor; Vozel, Benôıt

doi:10.1109/meco.2015.7181936

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…For the bpp case: if P 0 ∈ [0; 0.65], then bpp p = -165.9 ⋅ (P 0 ) 5 + 362.8 ⋅ (P 0 ) 4 -308.7 ⋅ (P 0 ) 3 + 130.3 ⋅ (P 0 ) 2 -32.85 ⋅ (P 0 ) + 6.969, (7) and if P 0 ∈ (0.65; 1], then the approximation is bpp = -0.4792 ⋅ (P 0 ) 2 -4.017 ⋅ (P 0 )+4.374.…”

Section: Proposed Methodology Of Providing a Desired Crmentioning

confidence: 99%

“…Nowadays, compression techniques become very important due to increasing amount of data acquired by new generations of remote sensing satellites, modern camcorders, cameras and other imaging processing sys tems [4,7]. Wherein, acquired images typically contain spatial and spectral (for multichannel and hyperspec tral images) redundancy [3,21] and they should be transmitted via telecommunication channels and/or stored.…”

Section: Introductionmentioning

confidence: 99%

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

Kozhemiakin,

Zemliachenko,

Lukin

et al. 2016

UJRS

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A novel compression ratio prediction and providing technique applicable to noisy and almost noise-free remote sensing images is proposed. It allows predicting and then providing a desired compression ratio for DCT-based coder in automatically manner. The proposed technique is algorithmically simple and has low computational complexity that allows using it onboard spaceborne or airborne carriers. The study is carried out for test and real-life Hyperion images. It is shown that the proposed technique has high accuracy and it is robust with respect to noise intensity and type. Relative error of prediction of providing compression ratio does not exceed 10%.

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Section: Proposed Methodology Of Providing a Desired Crmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Kozhemiakin,

Zemliachenko,

Lukin

et al. 2016

UJRS

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, for three-channel images, only preliminary analysis results showing that the OOP can exist were given [40]. Note that the results in [47] show that the OOP is more likely if multichannel noisy images are jointly compressed compared with component-wise compression. The possibility of predicting the existence of the OOP has been demonstrated in [36,40].…”

Section: Introductionmentioning

confidence: 99%

BPG-Based Lossy Compression of Three-Channel Noisy Images with Prediction of Optimal Operation Existence and Its Parameters

Коваленко

Vozel

2023

Remote Sensing

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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, dissemination, and transfer over communication lines where lossy compression techniques are more popular. The images to be compressed or some of their components are often noisy. They must therefore be compressed taking into account the properties of the noise. Due to the noise filtering effect obtained during lossy compression of noisy images, an optimal operating point (OOP) may exist. The OOP is a parameter that controls the compression for which the quality of the compressed image is closer (closest) to the corresponding noise-free image than the quality of the noisy (original, uncompressed) image according to some quantitative criterion (metric). In practice, it is important to know whether the OOP exists for a given image, because if the OOP exists, it is appropriate to perform the compression in the OOP or at least in its neighborhood. Since the real image is absent in practice, it is impossible to determine a priori whether the OOP exists or not. Here, we focus on three-channel-remote-sensing images and show that it is possible to easily predict the existence of the OOP. Furthermore, it is possible to predict the metric values or their improvements with appropriate accuracy for practical use. The BPG (better portable graphics) encoder is considered a special case of an efficient compression technique. As an initial design step, the case of additive white Gaussian noise with equal variance in the three components is considered. While previous research was mainly focused on predicting the improvement (reduction) of the PSNR and PSNR-HVS-M metrics, here we focus on the modern visual quality metrics, namely PSNR-HA and MDSI. We also discuss what to do if, according to the prediction, an OOP is absent. Examples of lossy compression of noisy three-channel remote sensing images are given. It is also shown that the use of three-dimensional compression provides a compression ratio increase by several times compared with component-wise compression in the OOP.

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“…Lossy compression of images with taking into account noise type [27] and characteristics has been paid considerable attention [28][29][30]. Possible existence of optimal operation point (OOP) and its prediction have been claimed and studied [13,18].…”

Section: Introductionmentioning

confidence: 99%

Lossy Compression of Remote Sensing Images with Controllable Distortions

Zemliachenko¹,

Krivenko²,

Vozel³

et al. 2019

Satellite Information Classification and Interpretation

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In this chapter, approaches to provide a desired quality of remote sensing images compressed in a lossy manner are considered. It is shown that, under certain conditions, this can be done automatically and quickly using prediction of coder performance parameters. The main parameters (metrics) are mean square error (MSE) or peak signal-to-noise ratio (PSNR) of introduced losses (distortions) although prediction of other important metrics is also possible. Having such a prediction, it becomes possible to set a quantization step of a coder in a proper manner to provide distortions of a desired level or less without compression/decompression iterations for single-channel image. It is shown that this approach can be also exploited in three-dimensional (3D) compression of multichannel images to produce a larger compression ratio (CR) for the same or less introduced distortions as for component-wise compression of multichannel data. The proposed methods are verified for test and real life images.

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Peculiarities of 3D compression of noisy multichannel images

Cited by 6 publications

References 10 publications

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

BPG-Based Lossy Compression of Three-Channel Noisy Images with Prediction of Optimal Operation Existence and Its Parameters

Lossy Compression of Remote Sensing Images with Controllable Distortions

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