Many papers have reviewed remote sensing image segmentation (RSIS) algorithms
currently. Those existing surveys are insufficiently exhaustive to sort out the various RSIS …

In this paper, we propose a multi-level thresholding model based on gray-level & local-
average histogram (GLLA) and Tsallis–Havrda–Charvát entropy for RGB color image. We …

Nature-inspired algorithms emulate the mathematical and innovative techniques for non-
linear and real-life problems worldwide. Imaging technology is emerging out as one of the …

Though traditional thresholding methods are simple and efficient, they may result in poor
segmentation results because only image's brightness information is taken into account in …

Thresholding is a popular method of image segmentation. Many thresholding methods
utilize only the gray level information of pixels in the image, which may lead to poor …

The image thresholding methods consume a lot of time due to computational complexity
when the number of threshold levels increases. In order to reduce computation time and …

In this article, a fast context-sensitive threshold selection technique is presented to solve the
image segmentation problems. In lieu of histogram, the proposed technique employs …

To improve the segmentation performance of thresholding methods, a novel strategy of
integrating the spatial information between pixel's is proposed in this paper. The proposed …

The rapid and accurate assessment of building damage states using only post-event remote
sensing data is critical when performing loss estimation in earthquake emergency response …

Image segmentation by thresholding is an important and fundamental task in image
processing and computer vision. In this paper, a new bi-level thresholding approach based …