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Dot Diffusion Block Truncation Coding for Satellite Image Retrieval

by Deepti Chavan, Kiran A. Bhandari
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 124 - Number 4
Year of Publication: 2015
Authors: Deepti Chavan, Kiran A. Bhandari
10.5120/ijca2015905447

Deepti Chavan, Kiran A. Bhandari . Dot Diffusion Block Truncation Coding for Satellite Image Retrieval. International Journal of Computer Applications. 124, 4 ( August 2015), 24-29. DOI=10.5120/ijca2015905447

@article{ 10.5120/ijca2015905447,
author = { Deepti Chavan, Kiran A. Bhandari },
title = { Dot Diffusion Block Truncation Coding for Satellite Image Retrieval },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 124 },
number = { 4 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 24-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume124/number4/22091-2015905447/ },
doi = { 10.5120/ijca2015905447 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:13:29.111487+05:30
%A Deepti Chavan
%A Kiran A. Bhandari
%T Dot Diffusion Block Truncation Coding for Satellite Image Retrieval
%J International Journal of Computer Applications
%@ 0975-8887
%V 124
%N 4
%P 24-29
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In present survey it is noticed that the profound interest in research and study of retrieval of satellite images and Image Retrieval on Content Based is grown hugely .Thus, to build the semantic error which is a huge challenge. Also, it prevents wide hosting of image on content based search engines which is now the necessity of CBIR technique. Mostly image search engine depend on human generated data as input query namely tags or annotations. The images get stored in database according to the annotations or tags assigned to them. Thus, tags or annotations are used as inputs by search engines .Thus, to overcome the limitation of annotations based image retrieval an Improved Block Truncation Coding is used which is based on Texture and color features of an image. In this paper, Improved Block Truncation Coding technique is used to fill the semantic gap. Then the similarity features type of search is carried to find different query regions namely desert, coastal, forest, metro from the satellite images. The retrieval technique can be practically applied and compared using different similarity methods .The technique of Improved Block Truncation Coding is described which is one of the most proficient methods used in retrieval of satellite images. Though, in traditional BTC certain redundancy like false contour, inherent artifacts are observed. In order to deal with this an improved BTC with dot- diffusion is applied to the system. Here, a Dot Diffusion is added for retrieving the most relevant images that best match to the query image whereas Dot Diffusion is used to give best quality image with good clearity and save memory need to store in database.

References
  1. M. Mese and P. P. Vaidyanathan, “Optimized half toning using dot diffusion and methods for inverse half toning,” IEEE Trans. Image Processing, vol. 9, no. 4, pp. 691–709, Apr. 2000
  2. G. Rafiee, S.S. Dlay, and W.L. Woo,” A Review of Content-Based Image Retrieval", IEEE, 2010. Tavel, P. 2007 Modeling and Simulation Design. AK Peters Ltd Tavel, P. 2007 Modeling and Simulation Design. AK Peters Ltd.
  3. Kekre H.B., Bharadi, V.A., Thepade S.D. , Mishra B.K., Ghosalkar, S.E., Sawant S.M. , "Content Based Image Retrieval Using Fusion of Gabor Magnitude and Modified Block Truncation Coding", IEEE computer society, 2010 IEEE.
  4. Dr.H.B.Kekre, S.D. Thepade et al.,"Image Retrieval with Shape Features Extracted using Gradient Operators and Slope Magnitude Technique with BTC",International Journal of Computer Applications (0975 – 8887) Volume 6– No.8, September 2010 Brown, L. D., Hua, H., and Gao, C. 2003. A widget framework for augmented interaction in SCAPE.
  5. Y N Mamatha and A.G Ananths and S 0 Neil, "Content Based Image Retrieval of Satellite Imageries Using Soft Query Based Color Composite Techniques",IEEE Trans on Acoustic speech signal processing, Vol I, No.3, pp. 1278- 1288, 1986
  6. Yu-f-x, Luo, H, Lu, Z-m"Colour image retrieval using pattern co-occurrence matrices based on BTC and VQ"IET Electronic Letters (Volume:47,   Spector, A. Z. 1989. Achieving application requirements. In Distributed Systems, S. Mullender
  7. Purohit Shrinivasacharya, Dr. M. V Sudhamani″Content Based Image Retrieval System using Texture and Modified Block Truncation Coding″2013 International Conference on Advanced Computing and Communication Systems (ICACCS -2013), Dec. 19–21,2003
  8. Delp, E. J., Saenz, M., and Salama, P., Block Truncation Coding(BTC),”Handbook of Image Bovik A.C ,Academic Press , pp. 176-181, 2000
  9. Dr. Fuhui Long, Dr. Hongjiang Zhang and Prof. David Dagan Feng, “Fundamentals of Content-Based Image Retrieval
  10. H B Kekre and V A Bharadi, “Modified BTC & Walsh coefficients Based Features for Content Based Image Retrieval” NCICT, India
  11. H.B.Kekre, S.D.Thepade “Image Retrieval using Augmented Block Truncation Coding Techniques” International Conference on Advances in Computing, Communication and Control (ICAC3’09)
  12. E. J. Delp and O. R. Mitchell, “Image compression using block truncation coding,” IEEE Trans. Communication., vol. 27, no. 9,pp. 1335–1342, Sep. 1979
Index Terms

Computer Science
Information Sciences

Keywords

Improved Block Truncation Coding (IBT Color ) Image Retrieval Block Truncation Coding (BTC) Satellite Image Retrieval (SIR) Dot Diffusion Block Truncation Coding (DDBTC).