Original Article

CNN-SICE Learner Based Image Contrast Enhancement

Year: 2020 | Month: June | Volume 8 | Issue 1

References (10)

1.Singh, P.K., Sangwan, O.P. and Sharma, A. 2013. A Systematic Review on Fault Based Mutation Testing Techniques and Tools for Aspect-J Programs, published in 3rd IEEE International Advance Computing Conference, IACC-2013 at AKGEC Ghaziabad, IEEE Xplore, pp. 1455–1461.

View at Google Scholar

2.Singh, P.K., Panda, R.K. and Sangwan, O.P. 2015. A Critical Analysis on Software Fault Prediction Techniques, published in World Applied Sciences Journal, 33(3): 371–379.

View at Google Scholar

3.Singh, P. K., Agarwal, D. and Gupta, A.2015. A Systematic Review on Software Defect Prediction, published in Computing for Sustainable Global Development (INDIACom), IEEE, pp. 1793– 97.

View at Google Scholar

4.Negi, S.S. and Bhandari, Y.S.2014. A hybrid approach to Image Enhancement using Contrast Stretching on Image Sharpening and the analysis of various cases arising using histogram, published in Recent Advances and Innovations in Engineering (ICRAIE), pp. 1–6.

View at Google Scholar

5.Wu, C., Liu, Z. and Jiang, H. 2014. Catenary image enhancement using wavelet-based contourlet transform with cycle translation, published in Optik. International Journal for Light and Electron Optics, 125(15): 3922–3925.

View at Google Scholar

6.Tripathi, R. and Gupta, N. 2018. A Review on Segmentation Techniques in Large-Scale Remote Sensing Images. International Journal Online of Science, 4(4), 2018. Retrieved from http://ijoscience.com/ ojsscience/index.php/ojsscience/article/view/143 . Date accessed: 18 December 2018.

View at Google Scholar

7.Wang, L.J. and Huang, Y.C. 2010. Non-linear image enhancement using opportunity costs, published in Second International Conference on Computational Intelligence Communication Systems and Networks (CICSyN), IEEE, pp. 256–261.

View at Google Scholar

8.Premkumar, S. and Parthasarathi, K.A.2014. An efficient approach for colour image enhancement using Discrete Shearlet Transform, published in 2nd International Conference on Current Trends in Engineering and Technology (ICCTET), IEEE, pp. 363–366.

View at Google Scholar

9.Shanmugavadivu, P. and Balasubramanian, K. 2014. Particle swarm optimized multi-objective histogram equalization for image enhancement, published in Optics Laser Technology, 57: 243–251.

View at Google Scholar

10.Jianrui Cai, Shuhang Gu, and Lei Zhang. 2018. “Learning a Deep Single Image Contrast Enhancer from Multi-Exposure Images”, IEEE Transactions on Image Processing, 27(4).

View at Google Scholar

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