Resampling Detection in Digital Images: A Survey Archana V
---
paper_title: Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue

paper_content:

This paper revisits the state-of-the-art resampling detector, which is based on periodic artifacts in the residue of a local linear predictor. Inspired by recent findings from the literature, we take a closer look at the complex detection procedure and model the detected artifacts in the spatial and frequency domain by means of the variance of the prediction residue. We give an exact formulation on how transformation parameters influence the appearance of periodic artifacts and analytically derive the expected position of characteristic resampling peaks. We present an equivalent accelerated and simplified detector, which is orders of magnitudes faster than the conventional scheme and experimentally shown to be comparably reliable.
---
paper_title: Blind Authentication Using Periodic Properties of Interpolation

paper_content:

In this paper, we analyze and analytically describe the specific statistical changes brought into the covariance structure of signal by the interpolation process. We show that interpolated signals and their derivatives contain specific detectable periodic properties. Based on this, we propose a blind, efficient, and automatic method capable of finding traces of resampling and interpolation. The proposed method can be very useful in many areas, especially in image security and authentication. For instance, when two or more images are spliced together, to create high quality and consistent image forgeries, almost always geometric transformations, such as scaling, rotation, or skewing are needed. These procedures are typically based on a resampling and interpolation step. By having a method capable of detecting the traces of resampling, we can significantly reduce the successful usage of such forgeries. Among other points, the presented method is also very useful in estimation of the geometric transformations factors.
---
paper_title: Detection of linear and cubic interpolation in JPEG compressed images

paper_content:

A novel algorithm is introduced that can detect the presence of interpolation in images prior to compression as well as estimate the interpolation factor. The interpolation detection algorithm exploits a periodicity in the second derivative signal of interpolated images. The algorithm performs well for a wide variety of interpolation factors, both integer factors and non-integer factors. The algorithm performance is noted with respect to a digital camera's "digital zoom" feature. Overall the algorithm has demonstrated robust results and might prove to be useful for situations where an original resolution of the image determines the action of an image processing chain.
---
paper_title: On Resampling Detection and its Application to Detect Image Tampering

paper_content:

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.
---
paper_title: Detection of linear and cubic interpolation in JPEG compressed images

paper_content:

A novel algorithm is introduced that can detect the presence of interpolation in images prior to compression as well as estimate the interpolation factor. The interpolation detection algorithm exploits a periodicity in the second derivative signal of interpolated images. The algorithm performs well for a wide variety of interpolation factors, both integer factors and non-integer factors. The algorithm performance is noted with respect to a digital camera's "digital zoom" feature. Overall the algorithm has demonstrated robust results and might prove to be useful for situations where an original resolution of the image determines the action of an image processing chain.
---
paper_title: On Resampling Detection and its Application to Detect Image Tampering

paper_content:

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.
---
paper_title: Blind Authentication Using Periodic Properties of Interpolation

paper_content:

In this paper, we analyze and analytically describe the specific statistical changes brought into the covariance structure of signal by the interpolation process. We show that interpolated signals and their derivatives contain specific detectable periodic properties. Based on this, we propose a blind, efficient, and automatic method capable of finding traces of resampling and interpolation. The proposed method can be very useful in many areas, especially in image security and authentication. For instance, when two or more images are spliced together, to create high quality and consistent image forgeries, almost always geometric transformations, such as scaling, rotation, or skewing are needed. These procedures are typically based on a resampling and interpolation step. By having a method capable of detecting the traces of resampling, we can significantly reduce the successful usage of such forgeries. Among other points, the presented method is also very useful in estimation of the geometric transformations factors.
---
paper_title: Detection of linear and cubic interpolation in JPEG compressed images

paper_content:

A novel algorithm is introduced that can detect the presence of interpolation in images prior to compression as well as estimate the interpolation factor. The interpolation detection algorithm exploits a periodicity in the second derivative signal of interpolated images. The algorithm performs well for a wide variety of interpolation factors, both integer factors and non-integer factors. The algorithm performance is noted with respect to a digital camera's "digital zoom" feature. Overall the algorithm has demonstrated robust results and might prove to be useful for situations where an original resolution of the image determines the action of an image processing chain.
---
paper_title: On Resampling Detection and its Application to Detect Image Tampering

paper_content:

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.
---
paper_title: On Resampling Detection and its Application to Detect Image Tampering

paper_content:

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.
---
paper_title: On Resampling Detection and its Application to Detect Image Tampering

paper_content:

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.
---
paper_title: A bibliography on blind methods for identifying image forgery

paper_content:

Verifying the integrity of digital images and detecting the traces of tampering without using any protecting pre-extracted or pre-embedded information have become an important and hot research field. The popularity of this field and the rapid growth in papers published during the last years have put considerable need on creating a complete bibliography addressing published papers in this area. In this paper, an extensive list of blind methods for detecting image forgery is presented. By the word blind we refer to those methods that use only the image function. An attempt has been made to make this paper complete by listing most of the existing references and by providing a detailed classification group.
---
paper_title: Detection of linear and cubic interpolation in JPEG compressed images

paper_content:

A novel algorithm is introduced that can detect the presence of interpolation in images prior to compression as well as estimate the interpolation factor. The interpolation detection algorithm exploits a periodicity in the second derivative signal of interpolated images. The algorithm performs well for a wide variety of interpolation factors, both integer factors and non-integer factors. The algorithm performance is noted with respect to a digital camera's "digital zoom" feature. Overall the algorithm has demonstrated robust results and might prove to be useful for situations where an original resolution of the image determines the action of an image processing chain.
---
paper_title: On Resampling Detection and its Application to Detect Image Tampering

paper_content:

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.
---
paper_title: On Resampling Detection and its Application to Detect Image Tampering

paper_content:

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.
---
paper_title: Improving re-sampling detection by adding noise

paper_content:

Current image re-sampling detectors can reliably detect re-sampling in JPEG images only up to a Quality Factor (QF) of ::: 95 or higher. At lower QFs, periodic JPEG blocking artifacts interfere with periodic patterns of re-sampling. We add a ::: controlled amount of noise to the image before the re-sampling detection step. Adding noise suppresses the JPEG ::: artifacts while the periodic patterns due to re-sampling are partially retained. JPEG images of QF range 75-90 are ::: considered. Gaussian/Uniform noise in the range of 28-24 dB is added to the image and the images thus formed are ::: passed to the re-sampling detector. The detector outputs are averaged to get a final output from which re-sampling can ::: be detected even at lower QFs. ::: We consider two re-sampling detectors - one proposed by Poposcu and Farid [1], which works well on uncompressed ::: and mildly compressed JPEG images and the other by Gallagher [2], which is robust on JPEG images but can detect only ::: scaled images. For multiple re-sampling operations (rotation, scaling, etc) we show that the order of re-sampling matters. ::: If the final operation is up-scaling, it can still be detected even at very low QFs.
---
paper_title: Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue

paper_content:

This paper revisits the state-of-the-art resampling detector, which is based on periodic artifacts in the residue of a local linear predictor. Inspired by recent findings from the literature, we take a closer look at the complex detection procedure and model the detected artifacts in the spatial and frequency domain by means of the variance of the prediction residue. We give an exact formulation on how transformation parameters influence the appearance of periodic artifacts and analytically derive the expected position of characteristic resampling peaks. We present an equivalent accelerated and simplified detector, which is orders of magnitudes faster than the conventional scheme and experimentally shown to be comparably reliable.
---
paper_title: Detecting Resized JPEG Images by Analyzing High Frequency Elements in DCT Coefficients

paper_content:

In this paper, we propose a method for detecting resized JPEG images. We defined 8 × 8 periodic blocks as JPEG blocks. JPEG block boundaries are detected by applying 8 × 8 block discrete cosine transform (DCT) to all the pixels of the input image and analyzing the high frequency coefficients in them. In order to quantitatively analyze the degree of forgery, we have developed two approaches such as truth-score and correlation-score methods. Experimental results using 375 original (untouched) JPEG images and 2,250 resized images recompressed with a variety of quality factors demonstrated that our proposed method can classify them with over 90% of accuracy. Our proposed method can detect not only conventional resizing but also state-of-the-art non-linear resizing such as seam carving.
---
paper_title: Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue

paper_content:

This paper revisits the state-of-the-art resampling detector, which is based on periodic artifacts in the residue of a local linear predictor. Inspired by recent findings from the literature, we take a closer look at the complex detection procedure and model the detected artifacts in the spatial and frequency domain by means of the variance of the prediction residue. We give an exact formulation on how transformation parameters influence the appearance of periodic artifacts and analytically derive the expected position of characteristic resampling peaks. We present an equivalent accelerated and simplified detector, which is orders of magnitudes faster than the conventional scheme and experimentally shown to be comparably reliable.
---
paper_title: Noise-Enhanced Detection of Micro-Calcifications in Digital Mammograms

paper_content:

The appearance of micro-calcifications in mammograms is a crucial early sign of breast cancer. Automatic micro-calcification detection techniques play an important role in cancer diagnosis and treatment. This, however, still remains a challenging task. This paper presents novel algorithms for the detection of micro-calcifications using stochastic resonance (SR) noise. In these algorithms, a suitable dose of noise is added to the abnormal mammograms such that the performance of a suboptimal lesion detector is improved without altering the detector's parameters. First, a SR noise-based detection approach is presented to improve some suboptimal detectors which suffer from model mismatch due to the Gaussian assumption. Furthermore, a SR noise-based detection enhancement framework is presented to deal with more general model mismatch cases. Our algorithms and the framework are tested on a set of 75 representative abnormal mammograms. They yield superior performance when compared with several classification and detection approaches developed in our work as well as those available in the literature.
---
paper_title: Detection of linear and cubic interpolation in JPEG compressed images

paper_content:

A novel algorithm is introduced that can detect the presence of interpolation in images prior to compression as well as estimate the interpolation factor. The interpolation detection algorithm exploits a periodicity in the second derivative signal of interpolated images. The algorithm performs well for a wide variety of interpolation factors, both integer factors and non-integer factors. The algorithm performance is noted with respect to a digital camera's "digital zoom" feature. Overall the algorithm has demonstrated robust results and might prove to be useful for situations where an original resolution of the image determines the action of an image processing chain.
---
paper_title: A bibliography on blind methods for identifying image forgery

paper_content:

Verifying the integrity of digital images and detecting the traces of tampering without using any protecting pre-extracted or pre-embedded information have become an important and hot research field. The popularity of this field and the rapid growth in papers published during the last years have put considerable need on creating a complete bibliography addressing published papers in this area. In this paper, an extensive list of blind methods for detecting image forgery is presented. By the word blind we refer to those methods that use only the image function. An attempt has been made to make this paper complete by listing most of the existing references and by providing a detailed classification group.
---
paper_title: Improving re-sampling detection by adding noise

paper_content:

Current image re-sampling detectors can reliably detect re-sampling in JPEG images only up to a Quality Factor (QF) of ::: 95 or higher. At lower QFs, periodic JPEG blocking artifacts interfere with periodic patterns of re-sampling. We add a ::: controlled amount of noise to the image before the re-sampling detection step. Adding noise suppresses the JPEG ::: artifacts while the periodic patterns due to re-sampling are partially retained. JPEG images of QF range 75-90 are ::: considered. Gaussian/Uniform noise in the range of 28-24 dB is added to the image and the images thus formed are ::: passed to the re-sampling detector. The detector outputs are averaged to get a final output from which re-sampling can ::: be detected even at lower QFs. ::: We consider two re-sampling detectors - one proposed by Poposcu and Farid [1], which works well on uncompressed ::: and mildly compressed JPEG images and the other by Gallagher [2], which is robust on JPEG images but can detect only ::: scaled images. For multiple re-sampling operations (rotation, scaling, etc) we show that the order of re-sampling matters. ::: If the final operation is up-scaling, it can still be detected even at very low QFs.
---
paper_title: Theory of the Stochastic Resonance Effect in Signal Detection: Part I—Fixed Detectors

paper_content:

In Part I of this paper [ldquoTheory of the Stochastic Resonance Effect in Signal Detection: Part I-Fixed Detectors,rdquo IEEE Transactions on Signal Processing, vol. 55, no. 7, pt. 1, pp. 3172-3184], the mechanism of the stochastic resonance (SR) effect for a fixed detector has been examined. This paper analyzes the stochastic resonance (SR) effect under the condition that the detector structure or its parameters can also be changed. The detector optimization problem with SR noise under both Neyman-Pearson and Bayesian criteria is examined. In the Bayesian approach when the prior probabilities are unknown, the minimax approach is adopted. The form of the optimal noise pdf along with the corresponding detector as well as the maximum achievable performance are determined. The developed theory is then applied to a general class of weak signal detection problems. Under the assumptions that the sample size N is large enough and the test statistics satisfies the conditions of central limit theorem, the optimal SR noise is shown to be a constant vector and independent of the signal strength for both Neyman-Pearson and Bayesian criteria. Illustrative examples are presented where performance comparisons are made between the original detector and the optimal SR noise modified detector for different types of SR noise.
---
paper_title: On Resampling Detection and its Application to Detect Image Tampering

paper_content:

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.
---
paper_title: Image Tampering Detection Using Bayer Interpolation and JPEG Compression

paper_content:

In this paper, we describe a technique to detect image tampering using two different methods. The first is based on the Bayer interpolation process and its consequences in the Fourier domain. The second uses artifacts of the JPEG compression and more particularly in the JPEG frame observable in the Fourier domain.
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Title: Resampling Detection in Digital Images: A Survey

Section 1: Introduction
Description 1: This section introduces the concept of resampling detection in digital images and its significance in the field of passive forgery detection.

Section 2: Resampling Detection Techniques
Description 2: This section discusses various techniques used for detecting resampling in digital images by analyzing the periodicity and other properties introduced during the resampling process.

Section 3: Properties of Second Difference
Description 3: This section explains the role of second order derivatives in identifying resampled images and how periodicity in second differences can be exploited for detection.

Section 4: Tamper Detection Using DCT High Pass Filtering
Description 4: This section covers the use of Discrete Cosine Transform (DCT) high pass filtering to identify inconsistencies in high frequency components of an image that has undergone resampling.

Section 5: Tamper Detection Using Wavelets
Description 5: This section describes how wavelet transforms can be used to detect resampled regions in an image by analyzing changes in high frequency content.

Section 6: Propescu & Farid's Method
Description 6: This section outlines the algorithm proposed by Propescu and Farid using expectation/maximization for identifying correlations in resampled signals.

Section 7: Rotation Tolerant Resampling Detection
Description 7: This section discusses methods developed to detect resampling even when the image has undergone rotation, focusing on the use of energy spectra.

Section 8: Resampling Detection on JPEG Images
Description 8: This section addresses the challenges and methods of detecting resampling in JPEG compressed images.

Section 9: Adding Noise to Suppress JPEG Blockiness
Description 9: This section elaborates on techniques to suppress JPEG artifacts by adding noise, making resampling patterns more detectable.

Section 10: Recompressed Resampling Detection
Description 10: This section explores the effects of recompression on resampling detection and methods to distinguish between original and recompressed images.

Section 11: Performance Analysis
Description 11: This section evaluates the performance of different resampling detection methods and discusses their strengths and weaknesses.

Section 12: Conclusions
Description 12: This section summarizes the findings of the survey, noting the limitations of current methods and suggesting areas for future research.