Date of Publication :23rd August 2017
Abstract: This paper gives a technique to enhance the contrast of low exposure gray image. For this threshold is calculated of gray image and it is utilized to clip the gray image into different images. And then this clipped image is individually equalized utilizing histogram equalization with discrete wavelet transform for the enhancement of the image.
Reference :
-
- Gonzalez, R.C., Woods, R.E., 2002. Digital Image Processing, second ed. Prentice Hall
- K. Singh, R. Kapoor, “Image enhancement via median-mean based sub-image clipped histogram equalisation”, Optik 125 (2014) 4646–4651.
- K. Singh, R. Kapoor, “Image enhancement using exposure based sub image histogram equalization”, Pattern Recogn., Lett. 36 (2014) 10–14.
- D. Kundur and D. Hatzinakos, “Digital watermarking for tell-tale tamper proofing and authentication,” Proceedings of the IEEE, vol. 87, issue 7, pp. 1167-1180, July 1999.
- Md Saiful Islam and Ui Pil Chong, “A Digital Image Watermarking Algorithm Based on DWT, DCT and SVD”, International Journal of Computer and Communication Engineering, Vol. 3, No. 5, September 2014
- Hanmandlu M, Verma O.P., Kumar N.K., Kulkarni M., 2009. “A novel optimal fuzzy system for color image enhancement using bacterial foraging”. IEEE Trans. Inst. Meas. 58 (8), 2867–2879.
- Kuldeep Singh, Rajiv Kapoor, “Image enhancement using Exposure based Sub Image Histogram Equalization”,2014 [8] Ooi, C.H., Kong, N.S.P., Ibrahim, H., 2009. “Bihistogram equalization with a plateau limit for digital image enhancement”, IEEE Trans. Consumer Electron. 55 (4), 2072–2080.
- Bhupendra Ram, “Digital Image Watermarking Technique Using Discrete Wavelet Transform And Discrete Cosine Transform”, International Journal of Advancements in Research & Technology, Volume 2, Issue4, April-2013 ISSN 2278-7763