Abstract
In the modern environment, digital image processing is a very vital area of research. It is a process in which an input image and output might be either any image or some characteristics. In image enhancement process, input image, therefore, results are better than given input image for any particular application or set of objectives. Traditional contrast enhancement technique results in lightning of image, so here Discrete Wavelet transform is applied on image and modify only Low–Low band. In this presented technique, for enhancement of given image having low contrast apply Brightness Preserving Dynamic Histogram Equalization (BPHDE), Discrete Wavelet Transform (DWT), Thresholding of sub-bands of DWT, Firefly Optimization and Singular Value Decomposition (SVD). DWT divides image into 4 bands of different frequency: High–high (HH), High–low (HL), Low–high (LH), and Low–low (LL). First apply a contrast enhancement technique named brightness preserving dynamic histogram equalization technique for enhancement of a given low-contrast image and boosts the illumination, then apply Firefly optimization on these 4 sub-bands and thresholding applied, this optimized LL band information and given input image’s LL band values are passed through SVD and new LL band obtained. Through inverse discrete wavelet transform of obtained new LL band and three given image’s HH, HL, and LH band obtained an image having high contrast. Quantitative metric and qualitative result of presented technique are evaluated and compared with other existing technique. A result reveals that presented technique is a more effective strategy for enhancement of image having low contrast. The technique presented by this study is simulated on Intel I3 64-bit processor using MATLAB R2013b.
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References
Kim, Y.T.: Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Trans. Consum. Electron. 43, 1–8 (1997)
Chen, S.D., Ramli, A.R.: Minimum mean brightness error bi-histogram equalization in contrast enhancement. IEEE Trans. Consum. Electron. 49, 1310–1319 (2003)
Chen, S., Ramli, A.: Preserving brightness in histogram equalizationbased contrast enhancement techniques. Digit. Signal Process. 14, 413–428 (2004)
Isa, N.A.M., Ooi, C.H.: Adaptive contrast enhancement methods with brightness preserving. IEEE Trans. Consum. Electron. 56, 2543–2551 (2010)
Kim, J.Y., Kim, L.S., Hwang, S.: An advanced contrast enhancement using partially overlapped sub-block histogram equalization. IEEE Trans. Circuits Syst. Video Technol. 11, 475–484 (2001)
Ibrahim, H., Kong, N.S.P.: Brightness preserving dynamic histogram equalization for image contrast enhancement. IEEE Trans. Consum. Electron. 53, 1752–1758 (2007)
Kim, T.K., Paik, J.K., Kang, B.S.: Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering. IEEE Trans. Consum. Electron. 44, 82–86 (1998)
Sun, C.C., Ruan, S.J., Shie, M.C., Pai, T.W.: Dynamic contrast enhancement based on histogram specification. IEEE Trans. Consum. Electron. 51, 1300–1305 (2005)
Wan, Y., Chen, Q., Zhang, B.M.: Image enhancement based on equal area dualistic sub-image histogram equalization method. IEEE Trans. Consum. Electron. 45, 68–75 (1999)
Wadud, M.A.A., Kabir, M.H., Dewan, M.A.A., Chae, O.: A dynamic histogram equalization for image contrast enhancement. IEEE Trans. Consum. Electron. 53, 593–600 (2007)
Demirel, H., Anbarjafari, G., Jahromi, M.N.: Image equalization based on singular value decomposition. In: Proceedings of 23rd IEEE International Symposium on Computer Information Science, Istanbul, Turkey, pp. 1–5 (2008)
Demirel, H., Ozcinar, C., Anbarjafari, G.: Satellite image contrast enhancement using discrete wavelet transform and singular value decomposition. IEEE Geosci. Remote Sens. Lett. 7, 333–337 (2010)
Demirel, H., Anbarjafari, G.: Discrete wavelet transform-based satellite image resolution enhancement. IEEE Trans. Geosci. Remote Sens. 49(6), 1997–2004 (2011)
Sunoriya, D., Singh, U.P., Ricchariya, V.: Image compression technique based on discrete 2-D wavelet transforms with arithmetic coding. Int. J. Adv. Comput. Res. 2(2), 92–99 (2012)
Shanna, N., Venna, O.P.: Gamma correction based satellite image enhancement using singular value decomposition and discrete wavelet transform. In: IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT) 2014. ISBN No. 978-1-4799-3914-5/14/$31.00 ©2014 IEEE
Akila, K., Jayashree, L.S., Vasuki, A.: A hybrid image enhancement scheme for mammographic images. Adv. Nat. Appl. Sci. 10(6), 26–29 (2016)
Priyadarshini, M., Sasikala, M.R. Meenakumari, R.: Novel Approach for Satellite Image Resolution and Contrast Enhancement Using Wavelet Transform and Brightness Preserving Dynamic Histogram Equalization. IEEE (2016)
Atta, R., Abdel-Kader, R.F.: Brightness preserving based on singular value decomposition for image contrast enhancement. Optik 126, 799–803 (2015)
Demirel, H., Anbarjafari, G.: Image resolution enhancement by using discrete and stationary wavelet decomposition. IEEE Trans. Image Process. 20(5), 1458–1460 (2011)
Bhandari, A.K., Soni, V., Kumar, A., Singh, G.K.: Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD. ISA Trans. 53, 1286–1296 (2014)
Agaian, S.S., Silver, B., Panetta, K.A.: Transform coefficient histogram-based image enhancement algorithms using contrast entropy. IEEE Trans. Image Process. 16, 741–758 (2007)
Gupta, P., Kumare, J.S., Singh, U.P., Singh, R.K.: Histogram based image enhancement techniques: a survey. Int. J. Comput. Sci. Eng. 5(6), 175–181 (2017)
Sheet, D., Garud, H., Suveer, A., Chatterjee, J., Mahadevappa, M.: Brightness preserving dynamic fuzzy histogram equalization. IEEE Trans. Consum. Electron. 56(4), 2475–2480 (2010). http://dx.doi.org/10.1109/TCE.2010.5681130
Satellite Image got from—http://www.satimagingcrop.com//
Rajesh, K., Harish, S., Suman: Comparative study of CLAHE, DSIHE & DHE schemes. Int. J. Res. Manag. Sci. Technol. 1(1)
Singh, U.P., Jain, S.: Modified chaotic bat algorithm-based counter propagation neural network for uncertain nonlinear discrete time system. Int. J. Comput. Intell. Appl. (World Scientific), SCI Index, IF: 0.62, 15 (3) (2016), 1650016. https://doi.org/10.1142/s1469026816500164
Singh, U.P., et. al.: Modified differential evolution algorithm based neural network for nonlinear discrete time system. In: Recent Developments in Intelligent Communication Applications. ISBN: 9781522517856
Atta, R., Ghanbari, M.: Low-contrast satellite images enhancement using discrete cosine transform pyramid and singular value decomposition. IET Image Proc. 7, 472–483 (2013)
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Kumare, J.S., Gupta, P., Singh, U., Singh, R.K. (2019). An Efficient Contrast Enhancement Technique Based on Firefly Optimization. In: Ray, K., Sharma, T., Rawat, S., Saini, R., Bandyopadhyay, A. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 742. Springer, Singapore. https://doi.org/10.1007/978-981-13-0589-4_17
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