Brightness preserving based on singular value decomposition for image contrast enhancement

Improved Air Light Estimation Algorithm by using Fuzzy Filters and Dark Channel with Large Haze Gradients

“…CNC(x, y) =h (e(x, y), CNI(y), CCI(y))…... (1) For the entire deviation trend of these three indexes, the statistical outcomes depict that the maximum value of CNI curve holds the normal outcome, but it is not inevitably the most effective fog removal impact. Nevertheless, the most effective outcome should have excellent naturalness (high CNI value).…”

“…That formula makes use of enhanced Gaussian union layout to enable you to take into account numerous combinations offering pure instinct in many challenging paying attention a glass windows, like observations in degree discontinuities which was 1 prevalent overuse injury in simple picture defogging. Zhiyuan Xu et al [1] have tried to think about that may, the best ways movie press collection improved for the more serious just by faults endure negative visibility. A new variance minimal flexible histogram equalization (CLAHE)-based procedure began to remove fog.…”

“…Where j(s) is the global normalized histogram of the processed image, i is the brightness level index, pi is the probability of occurrence of level i in the enhanced image [1]. …”

Intelligent Based Image Enhancement using Direct and In-Direct Contrast Enhancement Techniques – A Comparative Survey

“…One of the methods to extract the structural features of the original image is through SVD [27], [46]to preserve the mean brightness of the image. SVD of an image is normally represented in a matrix form, forming singular value matrix, providing the intensity information of the given image.…”

“…Also SVD is used to extract the structural features of the original image [27] and preserve the mean brightness of the image [46]. Reducing the noise present in the image is difficult and the methods are time consuming.…”