Implementation of Lossless Image Compression on Satellite Images using Microblaze Processor
Citation
Neethu Gopi, Sajitha A.S "Implementation of Lossless Image Compression on Satellite Images using Microblaze Processor", International Journal of Engineering Trends and Technology (IJETT), V45(6),272-275 March 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
In satellite communication, Satellite images are used to determine space information. Satellite images gets corrupted due to the channel noise, wrong ISO settings etc. Satellite images contains large amount of data which increases the size of image, due to huge size it requires more time for transmission and quality of images become degraded. To mitigate these problems in this project presents a simple design of a combined scheme for compression, denoising and fusion of satellite images. Lifting scheme is the simplest and efficient algorithm to calculate wavelet transforms. The use of lifting scheme to achieve image compression guaranteed to be lossless in presence of inaccuracies. Salt & Pepper noise is needed to corrupt the compressed image and median filter is used for denoising the image. Finally image fusion is carried out using maximum rule in high pass filter. This system is implemented in Xilinx platform studio with Microblaze soft core processor using System C language. This system achieves high image quality in terms of MSE and PSNR.
References
[1] P.Sendamarai., M.N Giriprasad , “FPGA implementation of Combined Compression & denoising scheme for remote sensing images”,IEEE International Conference On Recent Trends In Electronics Information Communication Technology, May 20-21, 2016.
[2] P.Sangeetha.,M.,Karthik,T.KalavathiDevi.,“VLSIArchitectures for the 4-Tap and 6-Tap 2-D Daubechies Wavelet Filters using Pipelined Direct Mapping Method” in:Proc. IEEE Int. Conf. on Information Embedded and Communication Systems(ICIIECS), 2015
[3] Nayna Vijaykumar Bhosale, Vandana B. Malode,” A Lifting Based DWT Scheme for Image Compression using VHDL”International Journal of Scientific Engineering and Technology Research Volume.03, IssueNo.06, May-2014.
[4] Ch. Sharath Kumar, D. Koteshwar Rao,“ Implementation of Image fusion by Lifting DWT using Micro-blaze Processor “,Inter National Journal of VLSI System Design and Communication System, November, 2014.
[5] A. Mayer, H.-P. Meinzer, “High performance medical image processing in client/server environments”, Comput. Meth. Prog. Biomed. 58 (1999) 207–217.
[6] G.Dinesh Kumar, P.Vijay Gopal, “An Efficient Removal Of Noise Using MDBUT Filter”, International Journal of Reviews on Recent Electronics and Computer Science (IJRRECS), October, 2013.
[7] https://en.wikipedia.org/wiki/Discrete_wavelet_transform
[8] https://en.wikipedia.org/wiki/Satellite_imagery
[9] Emin Kugu, “Satellite image denoising using Bilateral Filter with SPEA2 optimized parameters”, International Conference on Recent Advances in Space Technologies (RAST), 2013.
[10] S.Bhargav kuar,K.Esther Rani, “FPGA Implementation of 4D DWT and BPS based digital image watermarking”,International Journal of Engineering Trends and Technology(IJETT),V3(2):234-238,March-April,2012.
[11] Tilak Mukherjee, B.Y.V.N.R Swamy,M.V.L Bhavani,,”Robust Image Compression using Integer Wavelet transform Exploiting Lifting scheme”, International Journal of Engineering Trends and Technology(IJETT),V7(5):217-220,November,2014.
[12] G. Mamatha, V. Sumalatha, M.V. Lakshmaiah, “FPGA Implementation of Satellite Image Fusion Using Wavelet Substitution Method”, Science and Information Conference, July , 2015.
[13] C.Rajeswari, S.Prakasam, “Using Discrete Cosine Transform 2 to achieve High Peak Signal-to-Noise Ratio in Image Processing”, International Journal of Computer Applications (0975 – 8887) Volume 98– No.10, July, 2014.
[14] Varsha Dhakar, Jyotirmoy Pathak,“A Novel Parallel Architecture of Lifting based 2D Discrete Wavelet Transform”,IEEE International Conference on Computer, Communication and Control (IC4),2015.
[15] Poonam K.Patil, U. A. Patil, “Lossless Image Compression Via Lifting Scheme And SPIHT”, International Journal of Engineering Sciences & Research Technology, April, 2015.
Keywords
denoising, fusion of satellite images, lifting scheme, lossless image compression, median filter, System C language, Xilinx platform Studio.