A simple and reliable approach to providing a visually lossless image compression
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-03062-y.pdf
Reference45 articles.
1. Bull, D.R., Zhang, F.: Intelligent Image and Video Compression: Communicating Pictures, 2nd edn. Academic Press, Elsevier Ltd (2021)
2. Ince, I.F., Bulut, F., Kilic, I., Yildirim, M.E., Ince, O.F.: Low dynamic range discrete cosine transform (LDR-DCT) for high-performance JPEG image compression. Vis. Comput. 38, 1845–1870 (2022). https://doi.org/10.1007/s00371-022-02418-0
3. Hossain, K., Mantel, C., Forchhammer, S.O.: No-reference prediction of quality metrics for H.264-compressed infrared sequences for unmanned aerial vehicle applications. J. Electr. Imaging 28(4), 043012-1–14 (2019). https://doi.org/10.1117/1.JEI.28.4.043012
4. Krivenko, S., Krylova, O., Bataeva, E., Lukin, V.: Smart lossy compression of images based on distortion prediction. Telecommun. Radio Eng. 77(17), 1535–1554 (2018). https://doi.org/10.1615/TelecomRadEng.v77.i17.40
5. Saha, S., Vemuri, R.: An analysis on the effect of image features on lossy coding performance. IEEE Signal Process. Lett. 7(5), 104–107 (2000). https://doi.org/10.1109/97.841153
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