Chiman Kwan
ABSTRACT
In many bandwidth constrained applications, lossless compression may be unnecessary, as only two to three times of compression can be achieved. An alternative way to save bandwidth is to adopt perceptually lossless compression, which can attain eight times or more compression without loss of important information. In this research, our first objective is to compare and select the best compression algorithm in the literature to achieve 8:1 compression ratio with perceptually lossless compression for still images. Our second objective is to demonstrate error concealment algorithms that can handle corrupted pixels due to transmission errors in communication channels. We have clearly achieved the above objectives using realistic images.
- Ayhan, B and Kwan, C 2016 On the use of Radiance Domain for Burn Scar Detection under Varying Atmospheric Illumination Conditions and Viewing Geometry Journal of Signal, Image, and Video Processing, 11, p 605--612.Google Scholar
- Chang, C 2003 Hyperspectral Imaging, Kluwer Academic/Plenum Publishers.Google Scholar
- Daala, http://xiph.org/daala/Google Scholar
- Dao, M, Kwan, C, Koperski, K and Marchisio, G 2017 A Joint Sparsity Approach to Tunnel Activity Monitoring Using High Resolution Satellite Images, IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference, p 322--328.Google Scholar
- Dohner, J, Kwan, C and Ruggelbrugge, M 1996 Active Chatter Suppression in An Octahedral Hexapod Milling Machine: A Design Study, SPIE Smart materials & Structure Conference, vol. 2721.Google Scholar
- Elad, M 2010 Sparse and Redundant Representations, Springer New York. Google ScholarDigital Library
- JPEG, http://en.wikipedia.org/wiki/JPEG.Google Scholar
- JPEG-2000, http://en.wikipedia.org/wiki/JPEG_2000.Google Scholar
- JPEG-XR, http://en.wikipedia.org/wiki/JPEG_XR.Google Scholar
- Kwan, C and Luk, Y 2018 "Hybrid sensor network data compression with error resiliency," Data Compression Conference.Google Scholar
- Kwan, C and Zhou, J 2015 Method for Image Denoising, Patent #9,159,121.Google Scholar
- Kwan, C, Ayhan, B, Chen, G, Chang, C, Wang, J and Ji B 2006 A Novel Approach for Spectral Unmixing, Classification, and Concentration Estimation of Chemical and Biological Agents IEEE Trans. Geoscience and Remote Sensing, 44, p 409--419.Google ScholarCross Ref
- Kwan, C, Budavari, B, Dao, M and Zhou, J 2017 New Sparsity Based Pansharpening Algorithm for Hyperspectral Images IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference, p 88--93.Google Scholar
- Kwan, C, Li, B, Xu, R, Li, X, Tran, T and Nguyen, T Q 2006 A Complete Image Compression Codec Based on Overlapped Block Transform Eurosip Journal of Applied Signal Processing, p 1--15.Google Scholar
- Kwan, C, Li, B, Xu, R, Tran, T and Nguyen, T 2001 SAR Image Compression Using Wavelets Wavelet Applications VIII, Proc. SPIE (vol. 4391), p 349--357.Google Scholar
- Kwan, C, Yin, J, Zhou, J, Chen, H and Ayhan, B and 2013 Fast Parallel Processing Tools for Future HyspIRI Data Processing, NASA HyspIRI Science Symposium.Google Scholar
- Pan, G, Xu, H, Kwan, C, Liang, C, Haynes, L S and Geng, Z 1996 Modeling and Intelligent Chatter Control Strategies for a Lathe Machine," Control Engineering Practice, 4, p 1647--1658.Google ScholarCross Ref
- Ponomarenko, N, et al. 2007 On between-coefficient contrast masking of DCT basis functions Proc. of the Third International Workshop on Video Processing and Quality Metrics for Consumer Electronics.Google Scholar
- Qu, Y, Qi, H, Ayhan, B, Kwan, C and Kidd R 2017 Does Multispectral/Hyperspectral Pansharpening Improve the Performance of Anomaly Detection? IEEE International Geoscience and Remote Sensing Symposium, p 6130--6133.Google Scholar
- Strang G and Nguyen, T 1997 Wavelets and filter banks, Wellesley-Cambridge Press.Google Scholar
- Tran, T D, Liang, J and Tu, C 2003 Lapped transform via time-domain pre-and post-filtering IEEE Transactions on Signal Processing, 51, p 1557 - 1571. Google ScholarDigital Library
- Transformic,http://www.vision.ee.ethz.ch/~mansfiea/transfor mic/Google Scholar
- VP8, http://en.wikipedia.org/wiki/VP8.Google Scholar
- VP9, http://en.wikipedia.org/wiki/VP9.Google Scholar
- Wang, W, Li, S, Qi, H, Ayhan, B, Kwan, C and Vance, S 2015 Identify Anomaly Component by Sparsity and Low Rank, IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensor (WHISPERS).Google Scholar
- Wu, J, Liang, Q and Kwan, C 2012 A Novel and Comprehensive Compressive Sensing based System for Data Compression," Proc. IEEE Globecom, Anaheim, CA.Google Scholar
- X264, http://www.videolan.org/developers/x264.htmlGoogle Scholar
- X265, https://www.videolan.org/developers/x265.htmlGoogle Scholar
- Zhou, J and Kwan, C 2018 A Hybrid Approach for Wind Tunnel Data Compression Data Compression Conference, Snowbird, Utah, March 27--30.Google Scholar
- Zhou, J, Chen, H, Ayhan, B and Kwan, C 2012, A High Performance Algorithm to Improve the Spatial Resolution of HyspIRI Images NASA HyspIRI Science and Applications Workshop, Washington DC.Google Scholar
- Zhou, J, Kwan, C and Ayhan B 2017 Improved Target Detection for Hyperspectral Images Using Hybrid In-Scene Calibration, SPIE Journal of Applied Remote Sensing, 11.Google Scholar
Index Terms
- Perceptually Lossless Image Compression with Error Recovery
Recommendations
Perceptually Lossless Video Compression with Error Concealment
ICVISP 2018: Proceedings of the 2nd International Conference on Vision, Image and Signal ProcessingWe present a video compression framework that has several components. First, we aim at achieving perceptually lossless compression. Several well-known video codecs in the literature have been evaluated and the performance was assessed using several well-...
Lossless-by-Lossy Coding for Scalable Lossless Image Compression
This paper presents a method of scalable lossless image compression by means of lossy coding. A progressive decoding capability and a full decoding for the lossless rendition are equipped with the losslessly encoded bit stream. Embedded coding is ...
On performance of lossless compression for HDR image quantized in color space
High dynamic range (HDR) image requires a higher number of bits per color channel than traditional images. This brings about problems to storage and transmission. Color space quantization has been extensively studied to achieve bit encodings for each ...
Comments