Li et al., 2015 - Google Patents
Revealing the trace of high-quality JPEG compression through quantization noise analysisLi et al., 2015
- Document ID
- 15281390204069495796
- Author
- Li B
- Ng T
- Li X
- Tan S
- Huang J
- Publication year
- Publication venue
- IEEE Transactions on Information Forensics and Security
External Links
Snippet
To identify whether an image has been JPEG compressed is an important issue in forensic practice. The state-of-the-art methods fail to identify high-quality compressed images, which are common on the Internet. In this paper, we provide a novel quantization noise-based …
- 238000007906 compression 0 title abstract description 65
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30781—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F17/30784—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
- G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
- G06F17/30247—Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4642—Extraction of features or characteristics of the image by performing operations within image blocks or by using histograms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T1/00—General purpose image data processing
- G06T1/0021—Image watermarking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00711—Recognising video content, e.g. extracting audiovisual features from movies, extracting representative key-frames, discriminating news vs. sport content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/46—Embedding additional information in the video signal during the compression process
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2201/00—General purpose image data processing
- G06T2201/005—Image watermarking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Li et al. | Revealing the trace of high-quality JPEG compression through quantization noise analysis | |
| Wang et al. | Optimized feature extraction for learning-based image steganalysis | |
| Verma et al. | DCT-domain deep convolutional neural networks for multiple JPEG compression classification | |
| Kang et al. | Identifying tampered regions using singular value decomposition in digital image forensics | |
| Wang et al. | Exploring DCT coefficient quantization effects for local tampering detection | |
| Galvan et al. | First quantization matrix estimation from double compressed JPEG images | |
| Sadek et al. | Robust video steganography algorithm using adaptive skin-tone detection | |
| Li et al. | Statistical model of JPEG noises and its application in quantization step estimation | |
| WO2020228520A1 (en) | Image transformation method and device, storage medium and computer equipment | |
| Yang et al. | A clustering-based framework for improving the performance of JPEG quantization step estimation | |
| Yang et al. | Analyzing the effect of JPEG compression on local variance of image intensity | |
| Chandler et al. | Seven challenges for image quality research | |
| Kumar et al. | Near lossless image compression using parallel fractal texture identification | |
| Conotter et al. | Forensic detection of processing operator chains: Recovering the history of filtered JPEG images | |
| US9305603B2 (en) | Method and apparatus for indexing a video stream | |
| Yao et al. | An improved first quantization matrix estimation for nonaligned double compressed JPEG images | |
| Li et al. | Quantization step estimation for JPEG image forensics | |
| Jalali et al. | A new steganography algorithm based on video sparse representation | |
| CN105469353A (en) | Embedding method and device of watermark image, and extraction method and device of watermark image | |
| CN116471362A (en) | Digital video watermarking method and device, device and storage medium | |
| Bhartiya et al. | Forgery detection using feature-clustering in recompressed JPEG images | |
| CN103279914A (en) | A Method and Device for Image Compression Sensing Steganography Based on Leapfrog Optimization | |
| Cattaneo et al. | Experimental evaluation of an algorithm for the detection of tampered JPEG images | |
| Zhou et al. | A Survey of Perceptual Hashing for Multimedia | |
| Zhang et al. | Revealing the traces of nonaligned double JPEG compression in digital images |