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Reversible Denoising and Lifting Based Color Component Transformation for Lossless Image Compression [article]

Roman Starosolski
2016 arXiv   pre-print
To remove correlation without increasing noise, we integrate denoising into the lifting steps and obtain a reversible image component transformation.  ...  For JPEG-LS, JPEG 2000, and JPEG XR algorithms in lossless mode, we find that the proposed method applied to the RDgDb color space transformation with a simple denoising filter is especially effective  ...  Acknowledgments We thank Tytus Bernas, Piotr Fabian, and the anonymous reviewers for their constructive comments.  ... 
arXiv:1508.06106v2 fatcat:rs6iclbmlngh3jgsokappsog3y

A mixture of Noise Image Denoising using Sevenlets Wavelet Techniques

Beera Babu Srinivas Kumar, Periyapattinam Srinivasaiah Satyanarayana
2022 Trends in Sciences  
For the testing purpose Gaussian (G), Speckle (S), and Salt & Pepper (SP) noise added to the Lena image have been corrupted and denoised.  ...  The mixture of noises of 0.1, 1, and 10 % density noise (G+S) (Gaussian (G) pulse Speckle (S)), G+S+SP (Gaussian (G) plus Speckle (S) pulse Salt & Pepper (SP)) added to the Lena image and denoised, have  ...  communication engineering to eliminate noise at the transmitters and receivers during the uploading and downloading images, in medical diagnosis to obtain exact imagery because of noise will be present  ... 
doi:10.48048/tis.2022.4186 fatcat:i24qt3glqngsbpq7zkkrors4s4

Reversible denoising and lifting based color component transformation for lossless image compression

Roman Starosolski
2019 Multimedia tools and applications  
For the JPEG-LS, JPEG 2000, and JPEG XR standard algorithms in lossless mode, the application of RDLS to the RDgDb color space transformation with simple denoising filters is especially effective for images  ...  To remove correlation without increasing noise, a reversible denoising and lifting step (RDLS) was proposed that integrates denoising filters into LS.  ...  Acknowledgments The author thanks Tytus Bernaś, Piotr Fabian, and the anonymous reviewers for their constructive comments.  ... 
doi:10.1007/s11042-019-08371-w fatcat:ixrcrswhqfe5bndjev3ptteyhe

Image Noise and Digital Image Forensics [chapter]

Thibaut Julliand, Vincent Nozick, Hugues Talbot
2016 Lecture Notes in Computer Science  
This paper offers an overall review of digital image noise, from its causes and models to the degradations it suffers along the image acquisition pipeline.  ...  We show that by the end of the pipeline, the noise may have widely different characteristics compared to the raw image, and consider the consequences in forensic and counter-forensic imagery.  ...  Adding some noise on the falsified image will remove the quantization artefact and thus strongly decreases the double JPEG detection rate.  ... 
doi:10.1007/978-3-319-31960-5_1 fatcat:jytsorqb2vefbank7piooqi6fu

Determining digital image origin using sensor imperfections

Jan Lukas, Jessica Fridrich, Miroslav Goljan, Amir Said, John G. Apostolopoulos
2005 Image and Video Communications and Processing 2005  
Furthermore, it is possible to perform reliable identification even from images that underwent subsequent JPEG compression and/or resizing.  ...  The pattern noise is extracted from the images using a wavelet-based denoising filter.  ...  Special thanks belong to Taras Holotyak for providing us with Matlab code for the denoising filter.  ... 
doi:10.1117/12.587105 dblp:conf/eiivcp/LukasFG05 fatcat:qvetowpzd5fmra7vxedaw2yh6q

Impact of Benign Modifications on Discriminative Performance of Deepfake Detectors [article]

Yuhang Lu, Evgeniy Upenik, Touradj Ebrahimi
2021 arXiv   pre-print
In particular, the impact of benign processing operations such as transcoding, denoising, resizing and enhancement are not sufficiently studied.  ...  It quantitatively measures how and to which extent each benign processing approach impacts a state-of-the-art deepfake detection method.  ...  We evaluate a mixed operation that adds Gaussian noise first, followed by a denoising Gaussian filter. Interestingly, the additional denoising operation makes the result even worse.  ... 
arXiv:2111.07468v1 fatcat:rjjsam3xgngzdjigbqg5g73sce

Higher-Order, Adversary-Aware, Double Jpeg-Detection Via Selected Training On Attacked Samples

Mauro Barni, Ehsan Nowroozi, Benedetta Tondi
2018 Zenodo  
algorithm described in [17] , which removes the blocking artefacts of JPEG compression by applying a median filter followed by the addition of a Gaussian noise (dithering).  ...  INTRODUCTION Image forensic techniques for double JPEG detection in the presence of an adversary is one of the most widely studied topics in adversarial image forensics [1] , [2] .  ... 
doi:10.5281/zenodo.1159987 fatcat:ezwcu7q53jfq7ded5vkzp67guq

Detect and Defense Against Adversarial Examples in Deep Learning using Natural Scene Statistics and Adaptive Denoising [article]

Anouar Kherchouche, Sid Ahmed Fezza, Wassim Hamidouche
2021 arXiv   pre-print
In this paper, we proposea framework for defending DNN classifier against ad-versarial samples.  ...  The denoiser is based on block matching3D (BM3D) filter fed by an optimum threshold valueestimated by a convolutional neural network (CNN) toproject back the samples detected as AEs into theirdata manifold  ...  Some dropout layers are added to networks of color image datasets, i.e, CIFAR-10 and Tiny-ImageNet, with different rate to prevent over-fitting.  ... 
arXiv:2107.05780v1 fatcat:6giqdxccpzemremyo7mix3e4ya

Detecting digital image forgeries using sensor pattern noise

Jan Lukáš, Jessica Fridrich, Miroslav Goljan, Edward J. Delp III, Ping Wah Wong
2006 Security, Steganography, and Watermarking of Multimedia Contents VIII  
Our method is based on detecting the presence of the camera pattern noise, which is a unique stochastic characteristic of imaging sensors, in individual regions in the image.  ...  We present a new approach to detection of forgeries in digital images under the assumption that either the camera that took the image is available or other images taken by that camera are available.  ...  Special thanks belong to Taras Holotyak for providing us with Matlab code for the denoising filter. We would also like to thank Paul Blythe for many useful discussions.  ... 
doi:10.1117/12.640109 dblp:conf/sswmc/LukasFG06 fatcat:cxmv3jfp5bczjk6wsgwp6kttlu

Block Mean Modulation: An Effective and Robust Image Steganographic Technique in the Spatial Domain

A. NagalingaRajan, P. Eswaran, R. Sunder, S. Poonkuntran
2013 International Journal of Computer Applications  
The experimental results show that the message is preserved after applying common image modifications including jpeg compression, resizing and additive noise to some extent.  ...  Image steganography is one of the emerging techniques for secret communication in the digital age.  ...  Robustness against additive noise Additive Gaussian noise is added to the stego image and the integrity of the message is tested.  ... 
doi:10.5120/12992-0064 fatcat:ht2f5unczbc5rkoylquguljjpq

Digital Camera Identification From Sensor Pattern Noise

J. Luka, J. Fridrich, M. Goljan
2006 IEEE Transactions on Information Forensics and Security  
This is achieved by averaging the noise obtained from multiple images using a denoising filter.  ...  In this article, we propose a new method for the problem of digital camera identification from its images based on the sensor's pattern noise.  ...  We also tried to plant the noise extracted from a single Canon S40 image using the denoising filter [12] into a denoised Canon G2 image.  ... 
doi:10.1109/tifs.2006.873602 fatcat:e3ob5ctk5fgqrgufupj7742rtq

A New Approach to Improve Learning-based Deepfake Detection in Realistic Conditions [article]

Yuhang Lu, Touradj Ebrahimi
2022 arXiv   pre-print
This novel technique is deployed for deepfake detection tasks and has been evaluated by a more realistic assessment framework.  ...  The impact of conventional distortions and processing operations found in imaging workflows such as compression, noise, and enhancement are not sufficiently studied.  ...  Additive Gaussian Noise: For each batch of training data, a probability of 30% is adopted to add a Gaussian noise.  ... 
arXiv:2203.11807v1 fatcat:koy3tzpkjredhduvsn5mt6go2q

Resampling Detection in Digital Images: A Survey

Archana V.Mire, S. B. Dhok, N. J. Mistry, P. D. Porey
2013 International Journal of Computer Applications  
In [15] , Gaussian noise was used to denoise JPEG images.  ...  They further analyzed with Gaussian and Uniform noise and considered various re-sampling operations. They showed that noise added JPEG images behave similar to an uncompressed image.  ... 
doi:10.5120/14597-2838 fatcat:4l57gp7dprh6hbeijbdfgjkxja

Estimation and Restoration of Compositional Degradation Using Convolutional Neural Networks [article]

Kazutaka Uchida, Masayuki Tanaka, Masatoshi Okutomi
2018 arXiv   pre-print
Image restoration from a single image degradation type, such as blurring, hazing, random noise, and compression has been investigated for decades.  ...  In this paper, we propose a convolutional neural network (CNN) model for estimating the degradation properties of a given degraded image.  ...  degradations, i.e. , AWGN+JPEG compression for noise detection and blur+AWGN for blurlevel estimation.  ... 
arXiv:1812.09629v1 fatcat:efvvfkk4xzdd5g5j3vrhxvos64

Deep Learning for Detecting Processing History of Images

Mehdi Boroumand, Jessica Fridrich
2018 IS&T International Symposium on Electronic Imaging Science and Technology  
this article we explore this approach for the task of detecting the processing history of images.  ...  Our goal is to build a scalable detector for practical situations when an image acquired by a camera is processed, downscaled with a wide variety of scaling factors, and again JPEG compressed since such  ...  Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon.  ... 
doi:10.2352/issn.2470-1173.2018.07.mwsf-213 fatcat:t536mnm4vva4bbaje5t7l2357m
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