A Review of Various Categories of Satellite Image Processing in Remote Sensing

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 624)

Abstract

Satellite images may be unclear for many reasons. Consequently the important information in the images may not be easily seen. Image enhancement can improve a satellite image that has widespread information, but is not detectable. Image enhancement techniques are used to enhance the quality of the picture to get useful information, and many techniques have been developed to enhance the satellite images. Remote sensing technology has an important role for applications regarding the examination of the Earth. This chapter gives information and techniques useful for satellite image enhancement purposes. The general issues with satellite images are enhancement of gray scale image, noise, artifacts, distortion, resolution, less color information, and high frequency content, among others. Digital image processing is the basic concept distinctly preferred for satellite image processing. Essentially, satellite image processing information could be assembled into three types: (i) restoration, (ii) image rectification, and (iii) extracted data.

Keywords

Satellite images Image processing Image enhancement Information extraction Restoration 

References

  1. 1.
    P. Suganya, N. Mohanapriya, B. Kalaavathi, “Satellite image resolution enhancement using multi wavelet transform and comparison of interpolation techniques”, International Journal of Research in Engineering and Technology, (2014), eISSN: 2319-1163| pISSN: 2321-7308, Volume: 03 Special Issue: 07.Google Scholar
  2. 2.
    Rode, Gauri, and V. K. Shandilya. “A Literature Review of Satellite Image Enhancement Methods.” International Journal of Science and Research 5 pp: 506–509 (2016).Google Scholar
  3. 3.
    Pandya, Arpita, and Priya R. Swaminarayan. “CLASSIFICATION OF VEGETATION AREA FROM SATELLITE IMAGES USING IMAGE PROCESSING TECHNIQUES.” International Journal of Research in IT, Management and Engineering, (2015), ISSN 2249-1619, Impact Factor: 4.433, Volume 5, Issue 3 (2015).Google Scholar
  4. 4.
    Sharma, Aditi, and Ajay Khunteta. “Satellite image contrast and resolution enhancement using discrete wavelet transform and singular value decomposition.” In Emerging Trends in Electrical Electronics & Sustainable Energy Systems (IEEE), International Conference on, pp. 374–378., (2016).Google Scholar
  5. 5.
    Kumar, Gautam, P. Parth Sarthi, Prabhat Ranjan, and R. Rajesh. “Performance of k-means based satellite image clustering in RGB and HSV color space.” In Recent Trends in Information Technology (2016), International Conference on, pp. 1–5, 2016.Google Scholar
  6. 6.
    Oudaya Coumar, S., R. Aravindraja, S. Arulambalam, R. Raam Naaraayan, and R. Senthil Prasad. “Contrast enhancement of satellite images using advanced block based DWT technique.” In Recent Trends in Information Technology, (2016) International Conference on, pp. 1–6, IEEE.Google Scholar
  7. 7.
    Santha, T. “The significance of Real-time, biomedical and satellite Image Processing in understanding the objects & application to Computer Vision.” In Engineering and Technology, 2016 International Conference on, (IEEE), pp. 661–670.Google Scholar
  8. 8.
    Chandrakala, M., and Mrs R. Amsaveni. “Classification of Remote Sensing Image Areas Using Surf Features and Latent Dirichlet Allocation.” ijarcsse 3, (2013), no. 9.Google Scholar
  9. 9.
    Eastman, J. R. “Introduction to remote sensing and image processing.” Idrisi for Windows User’s Guide. (2001), Cap 3.Google Scholar
  10. 10.
    Sreenivas, B., B. Narasimha Chary, and INDIA KARIMNAGAR. “Processing Of Satellite Image Using Digital Image Processing.” In A world forum on Geospatial. (2011).Google Scholar
  11. 11.
    Radhadevi, P. V., V. Nagasubramanian, Archana Mahapatra, S. S. Solanki, Krishna Sumanth, and Geeta Varadan. “Potential of high-resolution Indian remote sensing satellite imagery for large scale mapping.” In ISPRS Hannover Workshop, ‘High-Resolution Earth Imaging for Geospatial Information,’ June, (2009), pp. 2–5.Google Scholar
  12. 12.
    Dalmiya, C. P., and V. S. Dharun. “A survey of registration techniques in remote sensing images.” Indian Journal of Science and Technology 8, (2015) Vol no. 26.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceChandigarh Group of CollegesMohaliIndia

Personalised recommendations