• MANJOT KAUR

Image enhancement plays an important role in remote sensing based vision applications. Recently, many techniques have already been proposed for enhancing the digital images. However, the existing techniques suffer from some limitations like edge, spectral, and spatial distortions. To overcome the limitations, a new technique is proposed which will evaluate k factor automatically using the ant colony optimization (ACO). ACO finds the best similarity value among the given set of values which represents the image in more efficient manner. The proposed approach have the ability to boost the contrast in digital images. It is also utilizing the modified edge preserving smoothing hypothesis based adaptive k-fuzzy image enhancement algorithm. The proposed approach has ability to reduce the effectuation of noise and preserves the edges in efficient manner. From the result analyses, it has been found that the proposed approach outperforms over the other techniques.

Image enhancement, Spatial domain methods, Frequency domain methods. Sharpening associated, Image Registration for Remote-sensing.

"Remote Sensing Image Enhancement Technique Using Modified Fuzzy Based T-2 Bell Shaped Membership Function", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.649-655, June 2019, Available :http://www.jetir.org/papers/JETIR1907H95.pdf

"Remote Sensing Image Enhancement Technique Using Modified Fuzzy Based T-2 Bell Shaped Membership Function", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp649-655, June 2019, Available at : http://www.jetir.org/papers/JETIR1907H95.pdf