Upgraded Dominant Brightness Level based Image Enhancement using Illuminate Normalization

Image enhancement is an algorithm used in vision applications for improving the visibility of the digital images. Recently much work is done in the field of remote sensing images to improve the visibility for improving their accuracy for further applications. It has been found that the most of the existing researchers have neglected many issues i.e. no technique is accurate for different kind of circumstances. The existing methods have neglected the use of radiant optimization to reduce the problem of noise which will be presented in the image. It is also found that the color artifacts which will be presented in the output image due to the transform domain methods, also neglected by the most of the researchers Therefore, to overcome these issues, in this work, the present research work uses Dominant Brightness Level Analysis (DBLA) based image enhancement algorithm using Illuminated normalization for removing the uneven brightness of the images, Gradient optimization to preserve edges of enhanced images and Adaptive histogram stretching to remove the color artifacts. Moreover the performance of DBLA and proposed DBLA technique for enhancing the remote sensed color images has also been evaluated. The comparison has been done on the basis of various performance metrics which proves the efficiency of the proposed algorithm.