Low-complexity open-loop coding of IDR infrared images having JPEG compatibility
Tóm tắt
In this paper, we present a low-complexity open-loop Intermediate Dynamic Range (IDR) infrared image coding algorithm which provides two scalability layers. The first layer corresponds to a low dynamic range (LDR) version of the image which can be obtained by a JPEG decoder, while the second layer corresponds to the original IDR image. To achieve bit-depth scalability, we separate an input IDR image into LDR and residual images by simple operations, so that the residual image has a bit depth not higher than 8 bits per pixel, i.e., it can be compressed by JPEG baseline or other coding algorithm, developed for 8-bit depth formats. For real-time applications, we introduce a predefined look-up table containing quality factors for both the LDR and the residual images, so that increase of the table index corresponds to reduction of bit rate and increase of distortion close to an operational rate-distortion curve. Experimental results show that the proposed algorithm is significantly less complex than JPEG-XT Profile C, part 6, and provides better coding performance than its reference software with default tone mapping operator for the vast majority of the infrared test images.
Tài liệu tham khảo
Friman, O., et al.: Methods for large-scale monitoring of district heating systems using airborne thermography. IEEE Trans. Geosci. Remote Sens. 52(8), 5175–5182 (2014)
Xu, Y., Wang, X., et al.: Thermal anomaly detection based on saliency computation for district heating system. In: 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (2016)
Belyaev, E., Forchhammer, S.: Drone HDR infrared video coding viaAerial map prediction. In: IEEE International Conference on ImageProcessing (ICIP) (2018)
Jose, A., Berni, J., et al.: Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Trans. Geosci. Remote Sens. 47(3), 722–738 (2009)
Millikan, B., Dutta, A., et al.: Fast detection of compressively sensed IR targets using stochastically trained least squares and compressed quadratic correlation filters. IEEE Trans. Aerosp. Electron. Syst. 53(5), 2449 (2017)
Hu, Hai-Miao, Wu, Jiawei, et al.: An adaptive fusion algorithm for visible and infrared videos based on entropy and the cumulative distribution of gray levels. IEEE Trans. Multimed. 19(12), 2706–2719 (2017)
Akil, M., Grandpierre, T., Perroton, L.: Real-time dynamic tone-mapping operator on GPU. J. Real Time Image Process. 7(3), 165–172 (2012)
Liu, J., Hassan, F., Carletta, J.E.: A study of hardware-friendly methods for gradient domain tone mapping of high dynamic range images. J. Real Time Image Process. 12(1), 165–181 (2016)
ITU-T and ISO/IEC JTC 1: JPEG 2000 image coding system: core coding system, ITU-T recommendation T. 800 and ISO/IEC 15444-1. JPEG 2000 Part 1, (2000)
Mai, Zicong, Mansour, H., et al.: Visually favorable tone-mapping with high compression performance in bit-depth scalable video coding. IEEE Trans. Multimed. 15(7), 1503–1518 (2013)
Le Pendu, M., Guillemot, C., Thoreau, D.: Local inverse tone curve learning for high dynamic range image scalable compression. IEEE Trans. Image Process. 24(12), 5753–5763 (2015)
High Efficiency Video Coding, document ITU-T Rec. H.265 and ISO/IEC 23008-2, Oct. 2014 . ISO/IEC 18477. Scalable compression and coding of continuous-tone still images (JPEG-XT). JTC 1 / SC 29 / WG 1, (2016)
Artusi, A., Mantiuk, R.K., Richter, T., et al.: Overview and evaluation of the JPEG XT HDR image compression standard. J. Real Time Image Process. 16(2), 413–428 (2015)
Richter, T.: On the standardization of the JPEG XT image compression. In: 2013 Picture Coding Symposium (PCS) (2013)
Richter, T.: Error bounds for HDR image coding with JPEG XT. In: 2017 Data Compression Conference (DCC) (2017)
Ward, G., Simmons, M.: JPEG-HDR: a backwards-compatible, high dynamic range extension to JPEG. In: Proceedings of the Thirteenth Color Imaging Conference (2005)
Wang, Z., Simon, S., et al.: Visually lossless image compression extension for JPEG based on just-noticeable distortion evaluation. In: 2015 International Conference on Systems, Signals and Image Processing (IWSSIP) (2015)
Choi, S., Kwon, O., et al.: Performance evaluation of JPEG XT standard for high dynamic range image coding. In: Proceedings of the World Congress on Engineering (2015)
Pinheiro, A., Fliegel, K., et al.: Performance evaluation of the emerging JPEG XT image compression standard. In: Proceedings of the 16th International Workshop on Multimedia Signal Processing (2014)
JPEG-XT reference software, [Online] https://jpeg.org/jpegxt/software.html. Accessed 12 Aug 2019
Shen, M., Xue, P., Wang, C.: Down-sampling based video coding using super-resolution technique. IEEE Trans. Circuits Syst. Video Technol. 21(6), 755 (2011)
Reinhard, E., Devlin, K.: Dynamic range reduction inspired by photoreceptor physiology. IEEE Trans. Vis. Comput. Gr. 11(1), 13–24 (2004)
Dufaux, F., le Callet, P., Mantiuk, R., Mrak, M.: High Dynamic Range Video: From Acquisition, to Display and Applications. Academic Press, Cambridge, MA (2016)
Chen, Y., Hao, P.: Integer reversible transformation to make JPEG lossless. In: 2004 7th international conference on signal processing (2004)
Bjontegaard, G.: Calculation of average PSNR differences between RD-curves (VCEG-M33). In: VCEG Meeting (ITU-T SG16 Q.6), Austin, Texas, USA (2001)
The Linköping Thermal InfraRed (LTIR) dataset, [Online] http://www.cvl.isy.liu.se/en/research/datasets/ltir/. Accessed 12 Aug 2019
ETH, [Online] http://projects.asl.ethz.ch/datasets/doku.php?id=ir:iricra2014. Accessed 12 Aug 2019
Bins, J., Draper, B., Bohm, W., Najjar, W.: Precision vs. error in JPEG compression. In: Parallel and Distributed Methods in Image Processing III, SPIE, vol. 3817 (1999)
Belyaev, E., Mantel, C., Forchhammer, S.: High bit depth infrared image compression via low bit depth codecs. In: SPIE Optical Engineering + Applications, Infrared Remote Sensing and Instrumentation XXV (2017)
Belyaev, E., Mantel, C., Forchhammer, S.: Low-complexity compression of high dynamic range infrared images with JPEG compatibility. In: IEEE Visual Communication and Image Processing, St. Petersburg, Florida (2017)
Richter, T., Simon, S.: Towards high-speed, low-complexity image coding: variants and modification of JPEG 2000. In: SPIE Applications of Digital Image Processing XXXV (2012)
HM Software, https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/. Accessed 12 Aug 2019
An open-source JPEG 2000 codec written in C, www.openjpeg.org/. Accessed 12 Aug 2019
Reinhard, E., Stark, M., Shirley, P., Ferwerda, J.: Photographic tone reproduction for digital images. ACM Trans. Gr. 21(3), 267–276 (2002)
Choi, S., Kwon, O., Lee, J., Kim, Y.: A JPEG backward-compatible image coding scheme for high dynamic range images. Dig. Signal Process. 67, 1–16 (2017)
Kwon, O., Choi, S., Shin, D.: Improvement of JPEG XT floating-point HDR image coding using region adaptive prediction. IEEE Access 6, 3321–3335 (2018)
Drago, F., Myszkowski, K., Annen, T., Chiba, N.: Adaptive logarithmic mapping for displaying high contrast scenes. Comput. Gr. Forum 22(3), 419–426 (2003)
Mai, Z., Mansour, H., et al.: Optimizing a tone curve for backward-compatible high dynamic range image and video compression. IEEE Trans. Image Process. 20(6), 1558–1571 (2011)
Mantiuk, R. et al.: HDR-VDP-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions. In: ACM Transactions on Graphics, vol. 30(4) (2011)
x265 HEVC Encoder / H.265 Video Codec, http://x265.org/. Accessed 12 Aug 2019
Minimalistic JPEG writer, https://www.jonolick.com. Accessed 12 Aug 2019