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Exploiting context dependence for image compression with upsampling
[article]
2020
arXiv
pre-print
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Image compression with upsampling encodes information to succeedingly increase image resolution, for example by encoding differences in FUIF and JPEG XL. ...
However, the currently used solutions rather do not exploit context dependence for encoding of such upscaling information. ...
Context dependence for symbol probability distribution is often exploited in the final symbol/bit sequence e.g. in CABAC [4] popular especially in video compression. ...
arXiv:2004.03391v3
fatcat:zfpdi2wiwzfpnpmpxbgzwz6lxi
Scalable Remote Rendering with Depth and Motion-flow Augmented Streaming
2011
Computer graphics forum (Print)
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But not only final images are of interest on the client side, auxiliary information like depth or motion become increasingly attractive in this context for various purposes. ...
., by depth, which is key to increase robustness with respect to data loss, image reconstruction, and is an important feature for stereo vision and other client-side applications. ...
Input edge image (left) has been processed with selected "inpainting" algorithms.
Figure 6 : 6 Compression prediction schemes. 1) Spatiotemporal contexts for edge-image compression. ...
doi:10.1111/j.1467-8659.2011.01871.x
fatcat:utsg7hmcmrhz5oh2bgavgsqhcm
Multi-Context Dual Hyper-Prior Neural Image Compression
[article]
2023
arXiv
pre-print
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Transform and entropy models are the two core components in deep image compression neural networks. ...
Most existing learning-based image compression methods utilize convolutional-based transform, which lacks the ability to model long-range dependencies, primarily due to the limited receptive field of the ...
[15] introduced a global reference context model that aims to exploit long-range dependencies. ...
arXiv:2309.10799v1
fatcat:uofokl67lfgt7njkbdz5ix2qb4
Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation
[article]
2019
arXiv
pre-print
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best model; and 52.5% mIOU on PASCAL Context. ...
In this work, we propose a data-dependent upsampling (DUpsampling) to replace bilinear, which takes advantages of the redundancy in the label space of semantic segmentation and is able to recover the pixel-wise ...
Acknowledgments The authors would like to thank Huawei Technologies for the donation of GPU cloud computing resources. ...
arXiv:1903.02120v3
fatcat:3wzquezhsjcptmnf7vadrijamy
Perceptual depth compression for stereo applications
2014
Computer graphics forum (Print)
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Abstract AUTHOR VERSION: Conventional depth video compression uses video codecs designed for color images. Given the performance of current encoding standards, this solution seems efficient. ...
To exploit the inherent limitations of human depth perception, we propose a novel depth compression method that employs a disparity perception model. ...
Visual-masking models lead to a significant bitrate reduction for color images [ZDL01, Wat93, RW96] . We explore their application in the context of disparity and depth compression. ...
doi:10.1111/cgf.12293
fatcat:thypuroyprbi5k4tdfvm4eom2y
Lossy Medical Image Compression using Residual Learning-based Dual Autoencoder Model
[article]
2021
arXiv
pre-print
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In this work, we propose a two-stage autoencoder based compressor-decompressor framework for compressing malaria RBC cell image patches. ...
The two latent space representations (first for the original image and second for the residual image) are used to rebuild the final original image. ...
Applying the principle of exploiting domain knowledge of image processing with the deep neural network architectures, proved to be better for image compression over conventional pre-deep learning era algorithms ...
arXiv:2108.10579v1
fatcat:2no5y3hvnvf4tbu3zyawmua4vq
Lossy Compression Approach to Transmultiplexed Images
2006
Proceedings Elmar
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Two cases are described and compared. the compression of combined image and the preliminary compression of input images before transmultiplexing. ...
The luminance of the transmitted image is calculated using formulae, which include both, upsampling and digital filtering. The combined image can be sent over a single transmission channel. ...
In such a system the rate of compression can be adapted to each of the image separately depending on needs. ...
doi:10.1109/elmar.2006.329568
fatcat:4ge2r32sefaithnugtt72zphwm
A novel Cross-Component Context Model for End-to-End Wavelet Image Coding
[article]
2023
arXiv
pre-print
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With CCM, the entropy model for the chroma latent space can be conditioned on previously coded components exploiting correlations in the learned wavelet space. ...
In this paper, we explore a promising alternative approach for neural compression, with an autoencoder whose latent space represents a nonlinear wavelet decomposition. ...
To exploit these correlations, we propose a novel cross-component context model (CCM) for the neural wavelet compression framework iWave++. ...
arXiv:2303.05121v1
fatcat:q6g2jdybrzcbroapgo2ht6lopa
Guest Editorial Introduction to the Special Issue on Recent Advances in Point Cloud Processing and Compression
2021
IEEE transactions on circuits and systems for video technology (Print)
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[A3] present a novel image synthesis method for effective point cloud attribute compression. ...
Finally, it assembles all the attribute images of patches by formulating it as a bin nesting problem and harvest an attribute image of the whole point cloud for image/video-based compression. ...
doi:10.1109/tcsvt.2021.3129071
fatcat:hw6chtchp5dzbacriqj7k4tz7q
EfficientFCN: Holistically-guided Decoding for Semantic Segmentation
[article]
2020
arXiv
pre-print
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Extensive experiments on PASCAL Context, PASCAL VOC, ADE20K validate the effectiveness of the proposed EfficientFCN. ...
However, the performances of existing encoder-decoder methods are far from comparable with the dilatedFCN-based methods. ...
Results on PASCAL Context The PASCAL Context dataset consists of 4,998 training images and 5,105 testing images for scene parsing. ...
arXiv:2008.10487v2
fatcat:vihntzp2z5fyffppg743lyasga
Transform recipes for efficient cloud photo enhancement
2015
ACM Transactions on Graphics
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With an equivalent transmission budget, they provide higher-quality results than JPEG-compressed input/output images, with a gain of the order of 10 dB in many cases. ...
(17 dB) download 41 kB apply enhancement apply recipe to high quality input CLOUD upsample & match histogram MOBILE DEVICE compressed input match histogram Figure 1 : Cloud computing is often thought as ...
Acknowledgements We thank the SIGGRAPH reviewers for their constructive comments. ...
doi:10.1145/2816795.2818127
fatcat:5muydd7uu5dexlt4j5tnrhsjpy
End-to-end Optimized Image Compression with Attention Mechanism
2019
Computer Vision and Pattern Recognition
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We present an end-to-end trainable image compression framework for low bit-rate and transparent image compression. ...
The prior probability of the latent representations is modeled by combining a hyperprior autoencoder and a Pixelcnn++ based context module and they are trained jointly with the transformation autoencoder ...
Conclusion In this paper, a novel deep learning based image compression framework with attention mechanism is designed for CLIC 2019 challenge. ...
dblp:conf/cvpr/ZhouSWW19
fatcat:btsnyrzfdrhondxfcqypqrhnmu
Variational Autoencoder based Image Compression with Pyramidal Features and Context Entropy Model
2019
Computer Vision and Pattern Recognition
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Variational autoencoder with the potential to address an increasing need for flexible lossy image compression, has recently be investigated as a promising direction for advancing the state-of-the-art. ...
Based on this effective framework, we present an end-to-end image compression method with a multi-scale encoder, residual decoder, and separate entropy model. ...
In future work, a more effective compression network with higher evaluation scores and less computational load will be exploited. Figure 1 . 1 Figure 1. Framework of image compression. ...
dblp:conf/cvpr/Wen19
fatcat:bjdx55cbhrdbbhd5tja5qbblfq
FADE: Fusing the Assets of Decoder and Encoder for Task-Agnostic Upsampling
[article]
2022
arXiv
pre-print
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over how each feature point contributes to upsampling kernels; iii) a decoder-dependent gating mechanism for enhanced detail delineation. ...
tasks such as image matting. ...
channel compression and standard convolution for kernel prediction. ...
arXiv:2207.10392v2
fatcat:b6usml3devactom5wrqhwoc77u
Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries
[article]
2019
arXiv
pre-print
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With advanced image journaling tools, one can easily alter the semantic meaning of an image by exploiting certain manipulation techniques such as copy-clone, object splicing, and removal, which mislead ...
Finally, decoder network learns the mapping from low-resolution feature maps to pixel-wise predictions for image tamper localization. ...
In our framework, we consider images as input so that the network can exploit global context. ...
arXiv:1903.02495v1
fatcat:bu6iacqbhvbbxboebyfwwu2qne
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