基于块效应谱分析的JPEG图像旋转角度估计

doi:10.16180/j.cnki.issn1007-7820.2023.09.007

摘要/Abstract

摘要：

图像旋转可以使图像伪造在几何角度上更加逼真,现有JPEG图像旋转角度估计算法的性能易受到块效应干扰和图像块尺寸大小影响,且对于旋转角度区间为[1°,15°]的估计仍然较为困难。文中提出了一种基于块效应谱分析的JPEG图像旋转角度估计算法:首先,使用变异蚁群算法提取图像的边缘并将其移除以突显块效应,并通过交叉差分进一步减轻图像纹理的影响;然后,通过设定合理的阈值和使用高斯高通滤波器移除傅里叶变换域的无关峰值,以减少干扰;最后,将傅里叶频谱的幅值分量投影到极坐标中,并将极坐标中峰值对应的极角作为旋转角度的估计值。实验结果表明,针对旋转角度位于[1°,15°]区间内的小尺寸JPEG图像检测,文中所提方法比现有方法具有更低的平均绝对误差。此外,当压缩质量因子逐渐下降时,文中所提算法的性能仍然优于现有方法,对JPEG压缩具有更好的鲁棒性。

关键词: 图像旋转角度估计, 重采样, JPEG图像块效应, 变异蚁群算法, 谱分析, 图像篡改, 图像取证, JPEG压缩

Abstract:

Image rotation makes fake images more realistic in geometric perspective, and the performance of existing JPEG image rotation angle estimation algorithms is easily disturbed by block artifacts and the image block size. It remains an imminent and challenging work for the rotation angle interval [1°,15°]. This study presents an effective algorithm to estimate the rotation angle of JPEG images based on block artifact spectral analysis. Firstly, the edges of the image are extracted and removed using a variant colony algorithm to highlight block effects. Secondly, the effect of image texture is further mitigated by cross-differentiation. Thirdly, extraneous peaks are removed in the Fourier transform domain by setting reasonable thresholds and using a Gaussian high-pass filter to reduce interference. Finally, the amplitude component of the Fourier spectrum is projected into the polar coordinates, and the polar angle corresponding to the peak in the polar coordinates is the estimation of rotation angle we need. The experimental results show that the average absolute error of the method is lower than that of the existing methods for the detection of small-size JPEG images whose rotation angle lies within the [1°,15°] interval. Besides, when the compression quality factor is gradually reduced, the performance of the proposed method is still better than the existing methods, and the robustness of the proposed method to JPEG compression is better.

Key words: image rotation angle estimation, resampling, JPEG block artifacts, variant colony algorithm, spectral analysis, image manipulation, image forensic, JPEG compression

中图分类号:

TP391.9

党良慧,张玉金. 基于块效应谱分析的JPEG图像旋转角度估计[J]. 电子科技, 2023, 36(9): 41-49.

DANG Lianghui,ZHANG Yujin. Rotation Angle Estimation of JPEG Images Using Block Artifact Spectrum Analysis[J]. Electronic Science and Technology, 2023, 36(9): 41-49.

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QF	方法	θ
QF	方法	1°	2°	3°	4°	5°	6°	7°	8°
90	文献[7]算法	72.921	68.847	64.689	60.739	51.642	40.543	32.775	21.121
	文献[9]算法	44.889	43.712	38.490	38.958	26.686	18.464	12.715	5.768
	文献[17]算法	19.538	17.062	17.399	12.284	10.677	8.479	15.621	11.513
	本文算法	4.342	3.524	4.395	1.781	3.649	1.952	3.941	1.865
80	文献[7]算法	76.352	71.139	67.365	62.893	50.342	38.534	29.262	20.917
	文献[9]算法	44.135	38.262	42.276	37.890	29.65	23.148	19.441	13.509
	文献[17]算法	16.783	16.709	15.589	11.503	13.075	13.155	13.493	11.413
	本文算法	3.331	2.783	2.685	4.775	3.661	3.009	2.085	1.123
70	文献[7]算法	73.907	71.307	64.503	62.897	51.273	42.466	28.337	17.324
	文献[9]算法	42.193	37.059	38.847	38.947	27.923	27.773	16.111	13.112
	文献[17]算法	17.984	16.65	15.966	11.029	10.169	9.416	12.423	13.076
	本文算法	3.589	2.825	3.667	1.786	2.982	1.885	2.165	1.669
60	文献[7]算法	78.133	73.465	65.62	62.956	50.46	39.359	23.334	18.195
	文献[9]算法	43.326	43.595	42.077	32.812	30.086	26.311	14.268	10.943
	文献[17]算法	19.659	15.708	13.892	8.517	14.791	11.378	8.069	11.322
	本文算法	2.281	3.698	2.465	1.511	0.608	1.104	1.011	2.691
50	文献[7]算法	81.723	73.233	68.343	58.823	44.016	34.353	21.235	13.892
	文献[9]算法	45.215	43.826	38.405	39.103	27.525	18.566	13.108	5.987
	文献[17]算法	21.068	21.412	19.404	14.153	12.002	15.764	14.013	13.844
	本文算法	3.089	2.467	1.443	2.388	0.806	1.094	1.007	0.713

QF	方法	θ
QF	方法	9°	10°	11°	12°	13°	14°	15°
90	文献[7]算法	16.298	12.374	12.600	20.246	16.248	18.031	17.300
	文献[9]算法	5.563	6.741	4.951	3.451	4.990	0.046	2.752
	文献[17]算法	11.972	14.635	7.729	12.461	13.770	13.743	8.854
	本文算法	1.147	1.007	1.035	1.689	0.969	0.859	1.096
80	文献[7]算法	16.025	10.186	9.564	18.643	716.820	16.843	16.456
	文献[9]算法	4.717	5.678	4.728	7.397	7.476	3.148	6.083
	文献[17]算法	14.854	11.076	10.865	12.249	8.882	12.821	6.796
	本文算法	2.974	1.911	0.813	0.682	0.755	1.082	0.612
70	文献[7]算法	17.894	11.579	12.409	15.986	14.524	14.696	17.346
	文献[9]算法	6.344	4.329	6.174	5.106	4.013	4.258	5.077
	文献[17]算法	10.546	13.291	9.531	10.376	7.882	10.046	13.107
	本文算法	0.878	0.718	0.945	1.574	0.695	1.023	0.717
60	文献[7]算法	15.559	10.941	15.452	16.437	17.134	15.903	18.737
	文献[9]算法	6.328	5.018	10.061	5.810	8.185	3.569	6.013
	文献[17]算法	8.534	8.072	5.354	9.041	7.503	8.031	2.065
	本文算法	1.239	1.041	1.104	0.576	1.177	0.927	0.642
50	文献[7]算法	13.168	10.500	12.084	15.675	15.037	15.915	14.206
	文献[9]算法	5.777	6.097	4.622	3.639	4.633	0.047	2.700
	文献[17]算法	9.792	15.408	11.915	14.127	14.198	12.031	10.664
	本文算法	0.738	1.348	0.804	0.509	0.887	0.736	0.522