Satellite image processing is one of the important research areas in the field of digital image processing and is a challenging task for the researchers. It is often required to remove noise and smooth the image to highlight certain features of interest for image analysis and extracting significant information from satellite images often termed as image enhancement. It is an important step for overall image recognition and interpretation process and is a pre processing step that serves as an important step towards the solution for image analysis. Image enhancement can be performed in spatial or frequency domains. In this paper, we focus on spatial domain enhancement techniques with respect to satellite images. Some of the important image enhancement techniques such as contrast stretching, decorrelation stretch, histogram equalization and contrast limited adaptive histogram equalization are experimented and compared for visual interpretability. Two parameters, Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR) are used for performance evaluation. The techniques are tested using 20 LandSat satellite images with different illumination effects. The experimentation was carried out using soft computing tool Matlab. It was observed that for satellite images, contrast stretching gives better results as compared to other techniques.

Image Enhancement; Contrast Stretching; Mean Squared Error (MSE); Peak Signal to Noise ratio (PSNR); Landsat Imagery

[1] G. Singh and A. Mittal, �Various Image Enhancement Techniques-A Critical Review�, International Journal of Innovation and Scientific Research, Vol. 10, No. 2, pp. 267�274, 2014.
[2] Ashamdeep Singh and Navdeep Kanwal, �Qualitative Comparative Study of Various Contrast Enhancement Techniques�, International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR), vol. 3, no. 1, pp. 19�24, 2013.
[3] J. Lisani, J. Michel, J. Morel, A. B. Petro, and C. Sbert, �An Inquiry on Contrast Enhancement Methods for Satellite Images�, IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 12, pp. 7044�7054, Dec 2016.
[4] M.A.Shaikh and S.B.Sayyad, �Color Image Enhancement Filtering Techniques for Agricultural Domain Using Matlab�, ISPRS International Symposium on �Operational Remote Sensing Applications: Opportunities, Progress and Challenges�, no. 224, Dec 9-12, 2014.
[5] P. Kaushik and Y. Sharma, �Comparison of different image enhancement techniques based upon Psnr & Mse�, International Journal of Applied Engineering Research, vol. 7, no. 11, pp. 2010�2014, 2012.
[6] �Remote Sensing-Digital Image Processing-Image Enhancement Filtering and edge enhancement�, Http://nptel.ac.in/courses/105108077/module4/lecture16.pdf, , pp. 1�19, Dec 10, 2016
[7] R. Aedla, �Satellite Image Contrast Enhancement Algorithm based on Plateau Histogram Equalization�, IEEE Region 10 Symposium, pp. 213�218, 2014.
[8] S. S. Al-amri, N. V Kalyankar, and S. D. Khamitkar, �Contrast Stretching Enhancement in Remote Sensing Image,� BIOINFO Sensor Networks, vol. 1, no. 1, pp. 06-09, 2011.
[9] B. Attachoo and P. Pattanasethanon, �A new approach for colored satellite image enhancement�, 2008 IEEE International Conference on Robotics and Biomimetics, Feb 21-26, pp. 1365�1370, 2009.
[10] B. D. Jadhav, �An Effective method for Satellite Image Enhancement�, IEEE International Conference on Computing and Automation (ICCCA2015), pp. 1171�1175, 2015.
[11] Ahire Rina B, V. S. Patil �Overview of Satellite Image Resolution Enhancement Techniques�, IEEE, pp. 0�3, 2013.
[12] P. Bidwai and D. J. Tuptewar, �Resolution and contrast enhancement techniques for grey level, color image and satellite image�, Proceedings - IEEE International Conference on Information Processing,, pp. 511�515, Dec 16-19, 2016.
[13] R. R. Naaraayan and R. S. Prasad, �Contrast Enhancement Of Satellite Images Using Advanced Block Based Dwt Technique�, IEEE International Conference on Recent Trends in Information Technology, 2016.
[14] S. Nimkar, S. Shrivastava, and S. Varghese, �Contrast Enhancement and Brightness Preservation Using Multi-Decomposition Histogram Equalization� Signal & Image Processing : An International Journal, vol. 4, no. 3, pp. 83�93, 2013.
[15] X. Sun, L. Zhang, H. Yang, T. Wu, Y. Cen, and Y. Guo, �Enhancement of Spectral Resolution for Remotely Sensed Multispectral Image�, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 5, pp. 2198�2211, 2015.
[16] R. P. Singh and M. Dixit, �Histogram Equalization : A Strong Technique for Image Enhancement�, International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 8, no. 8, pp. 345�352, 2015.
[17] V. Syrris, S. Ferri, D. Ehrlich, and M. Pesaresi, �Image Enhancement and Feature Extraction Based on Low-Resolution Satellite Data�, 1986 IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing vol. 8, no. 5, pp. 1�10, 2015.
[18] A. Vashisth, R. Sharma, �A Survey of Various Image Enhancement Methods on Different Types of Images�, International Journal of Computer Sciences and Engineering, vol. 3, Issue 2, pp. 10�14, 2015.
[19] R. C. Gonzalez and R. E. Woods, �Digital Image Processing�, Prentice-Hall, 3rd edition,ISBN:978-81-317-2695-2 , 2008.
[20] Thomas M. Lillesand, Ralph W. Kiefer, Jonathan W. Chipman, �Remote Sensing and Image Interpretation�, Wiley, 6th edition, ISBN 978-81-265-3223-0 , 2007.
[21] John A. Richards, Xiuping Jia, �Remote Sensing Digital Image Analysis-An Introduction�, Springer, 4th edition, ISBN-13 978-3-540-25128-6 2006.