Abstract
In this paper, we present a short review of some well-known image codecs in the literature and summarize a systematic study that determines the root cause of some puzzling observations in image compression experiments. Moreover, we propose a methodology to determine whether an image is genuine or not, meaning that whether or not a given image has been compressed and decompressed before and by which codec. In image compression class projects, students may observe some strange behaviors when they use some images with unknown quality in compression experiments. That is, some performance metrics from a mediocre codec such as JPEG may have exceptionally high values at certain compression ratios as compared to other high performing codecs. This confusing behavior may be overlooked by instructors, and students may never understand why this is happening. We will first highlight this anomalous behavior. We will then use experiments to systematically determine the root cause, which is due to image quality. In other words, if one uses a previously compressed and decompressed image in some compression experiments, it is highly likely that some strange behaviors in the performance metrics will show up. Our findings include the determination of the root cause of a puzzling phenomenon in image compression experiments and some sound advice to instructors, tutors, and students on how one can prevent such behaviors from occurring. We also developed a methodology to determine whether an image is genuine or not.
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References
Strang, G., Nguyen, T.: Wavelets and Filter Banks. Wellesley-Cambridge Press, Wellesley (1997)
Zhou, J., Kwan, C.: A Hybrid approach for wind tunnel data compression. In: Data compression conference (2018)
Kwan, C., Luk, Y.: Hybrid sensor network data compression with error resiliency. In: Data Compression Conference (2018)
Kwan, C., Larkin, J.: Perceptually lossless compression for mastcam images. In: IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference (2018)
Kwan, C., Larkin, J., Budavari, B., Chou, B.: Compression algorithm selection for multispectral Mastcam images. In: Signal & Image Processing: An International Journal (SIPIJ), (2019)
JPEG.: http://en.wikipedia.org/wiki/JPEG. Accessed 24 Dec 2018
JPEG-2000.: http://en.wikipedia.org/wiki/JPEG_2000. Accessed 24 Dec 2018
Du, Q., Fowler, J.E.: Hyperspectral image compression using JPEG2000 and principal component analysis. IEEE Geosci. Remote Sens. Lett. 4(2), 201–205 (2007)
X264.: http://www.videolan.org/developers/x264.html. Accessed 24 Dec 2018
X265.: https://www.videolan.org/developers/x265.html. Accessed 24 Dec 2018
Daala.: http://xiph.org/daala/. Accessed 24 Dec 2018
Kwan, C., Li, B., Xu, R., Li, X., Tran, T., Nguyen, T.Q.: A complete image compression codec based on overlapped block transform. EURASIP J. Appl. Signal Process. 2006, 1–15 (2006)
Tran, T.D., Liang, J., Tu, C.: Lapped transform via time-domain pre-and post-filtering. IEEE Trans. Signal Process. 51(6), 1557–1571 (2003)
Ponomarenko, N., Silvestri, F., Egiazarian, K., Carli, M., Astola, J., Lukin, V.: On between-coefficient contrast masking of DCT basis functions. In: Proceedings of the Third International Workshop on Video Processing and Quality Metrics for Consumer Electronics, Scottsdale, Arizona, USA, 25–26 January (2007)
Wu, H.R., Reibman, A., Lin, W., Pereira, F., Hemami, S.: Perceptual visual signal compression and transmission. Proc. IEEE 101(9), 2025–2043 (2013)
Uthayakumar, J., Vengattaraman, T., Dhavachelvan, P.: A survey on data compression techniques: from the perspective of data quality, coding schemes, data type and applications. J. King Saud Univ. Comput. Inf. Sci. (2018). https://doi.org/10.1016/j.jksuci.2018.05.006
Pennebaker, W.B., Mitchell, J.L.: JPEG–Still image data compression standard, Van Nostrand Reinhold. Springer, Berlin (1993)
JPEG-XR.: http://en.wikipedia.org/wiki/JPEG_XR
Kwan, C., Chou, B., Larkin, J., Budavari, B.: Perceptually Lossless Compression of Mastcam Images with Error Recovery. In: Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII Conference (2019)
Kwan, C., Li, B., Xu, R., Tran, T., Nguyen, T.: SAR image compression using wavelets. Wavelet Appl. VIII 4391, 349–357 (2001)
Acknowledgements
This research was supported in part by NASA under Contract 80NSSC17C0035. The views, opinions, and/or findings expressed are those of the author and should not be interpreted as representing the official views or policies of NASA or the US Government.
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Kwan, C., Larkin, J., Budavari, B. et al. A short review of well-known image codecs and observations and root cause of some strange behaviors in image compression codecs. SIViP 14, 583–591 (2020). https://doi.org/10.1007/s11760-019-01591-5
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DOI: https://doi.org/10.1007/s11760-019-01591-5