Parameter estimation of image gamma transformation based on zero-value histogram bin locations

Abstract Gamma transformation plays an important role in image processing and image display. However, images may look either bleached out or too dark if transformed with improper parameters. While the value of gamma transformation parameter with which an image was created is not included in the current image standards, it is hard to restore the original image vision without the knowledge of gamma transformation. In this paper, a gamma transformation parameter estimation method is proposed based on Zero-Value Histogram Bin (ZVHB) locations. The method firstly exploits the relationship between the number of ZVHBs and the parameter of gamma transformation to get an approximate value of the parameter and an interval to which the parameter belongs. Then in the interval, the parameter is searched from the approximate value by matching the ZVHB locations of the investigated image and the reference images transformed with two close parameters. The experimental results validate the effectiveness of the proposed method, which outperforms the state-of-the-art methods. Meanwhile, the improperly transformed images can be restored visually by applying inverse gamma transformation with the estimated parameters.

[1]  Yao Zhao,et al.  Detection of operation chain: JPEG-Resampling-JPEG , 2017, Signal Process. Image Commun..

[2]  Yong Ho Moon,et al.  Blind identification of image manipulation type using mixed statistical moments , 2015, J. Electronic Imaging.

[3]  Yao Zhao,et al.  Contrast Enhancement-Based Forensics in Digital Images , 2014, IEEE Transactions on Information Forensics and Security.

[4]  Qingzhong Liu,et al.  An approach to detecting JPEG down-recompression and seam carving forgery under recompression anti-forensics , 2017, Pattern Recognit..

[5]  Yao Zhao,et al.  Forensic estimation of gamma correction in digital images , 2010, 2010 IEEE International Conference on Image Processing.

[6]  Yao Zhao,et al.  Robust median filtering detection based on local difference descriptor , 2017, Signal Process. Image Commun..

[7]  Min Wu,et al.  Digital image forensics via intrinsic fingerprints , 2008, IEEE Transactions on Information Forensics and Security.

[8]  Sam Kwong,et al.  An Effective Method for Detecting Double JPEG Compression With the Same Quantization Matrix , 2014, IEEE Transactions on Information Forensics and Security.

[9]  Mauro Barni,et al.  A Universal Attack Against Histogram-Based Image Forensics , 2013, Int. J. Digit. Crime Forensics.

[10]  K. J. Ray Liu,et al.  Forensic estimation and reconstruction of a contrast enhancement mapping , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[11]  Xinpeng Zhang,et al.  Estimation of Image Rotation Angle Using Interpolation-Related Spectral Signatures With Application to Blind Detection of Image Forgery , 2010, IEEE Transactions on Information Forensics and Security.

[12]  Mauro Barni,et al.  Second-Order Statistics Analysis to Cope With Contrast Enhancement Counter-Forensics , 2015, IEEE Signal Processing Letters.

[13]  Yuewei Dai,et al.  Detect image splicing with artificial blurred boundary , 2013, Math. Comput. Model..

[14]  Hany Farid,et al.  Blind inverse gamma correction , 2001, IEEE Trans. Image Process..

[15]  Yu-Ju Lin,et al.  A patch analysis method to detect seam carved images , 2014, Pattern Recognit. Lett..

[16]  Alessandro Piva,et al.  Detection of Nonaligned Double JPEG Compression Based on Integer Periodicity Maps , 2012, IEEE Transactions on Information Forensics and Security.

[17]  Kang Hyeon Rhee.  Median filtering detection using variation of neighboring line pairs for image forensics , 2016, J. Electronic Imaging.

[18]  Yao Zhao,et al.  Edge-based Blur Metric for Tamper Detection , 2010, J. Inf. Hiding Multim. Signal Process..

[19]  Timothy K. Shih,et al.  Tamper Detection of JPEG Image Due to Seam Modifications , 2015, IEEE Transactions on Information Forensics and Security.

[20]  Dongming Wang,et al.  Blur Detection of Digital Forgery Using Mathematical Morphology , 2007, KES-AMSTA.

[21]  Ricardo L. de Queiroz,et al.  Identification of bitmap compression history: JPEG detection and quantizer estimation , 2003, IEEE Trans. Image Process..

[22]  Hai-Dong Yuan,et al.  Blind Forensics of Median Filtering in Digital Images , 2011, IEEE Transactions on Information Forensics and Security.

[23]  K. J. Ray Liu,et al.  Detectability of the Order of Operations: An Information Theoretic Approach , 2016, IEEE Transactions on Information Forensics and Security.

[24]  K. J. Ray Liu,et al.  Forensic detection of image manipulation using statistical intrinsic fingerprints , 2010, IEEE Transactions on Information Forensics and Security.

[25]  V. Mankar,et al.  Blind method for rescaling detection and rescale factor estimation in digital images using periodic properties of interpolation , 2014 .