• SONIA RANI

Abstract: In existing technique only using the concept of vector optimization to enhance the resolution of an image from low to high, which is not give satisfying and accurate results which are very time consuming as well. For the cure, the previous shortcomings we introduce a new proposed algorithm for image resolution. In our proposed result, we make a combination of clustering techniques and regression functions to enhance an image in digital image processing. In our research, we made the clusters of low-resolution features from an image and collect in a cluster of similar type. With the use clustering we easily find exact, we use the kernel regression for convert a low-resolution image to high-resolution image and improve the accuracy of the image and it less time consuming. Which give us better result as compare to the previous technique.

Digital image processing, low resolution image, K-MEANS clustering, Kernel regression, image enhancement, pixel resolution, time, computational complexity,accuracy

"Improved Algorithm for Spatial Resolution for an image using Kernel Regression and K-Mean ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.963-973, June 2019, Available :http://www.jetir.org/papers/JETIR1906U30.pdf

"Improved Algorithm for Spatial Resolution for an image using Kernel Regression and K-Mean ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp963-973, June 2019, Available at : http://www.jetir.org/papers/JETIR1906U30.pdf