Multilevel Thresholding (MLT) is considered as a significant and imperative research field in image segmentation that can efficiently resolve difficulties aroused while analyzing the segmented regions of multif
Multilevel Thresholding (MLT) is considered as a significant and imperative research field in image segmentation that can efficiently resolve difficulties aroused while analyzing the segmented regions of multifaceted images with complicated nonlinear conditions. MLT being a simple exponential combinatorial optim...
Introduction Compressed sensing (CS) [1,2] and sparse representation [3,4] have been widely used in the field of wireless communications [5–7] and image processing [8–10]. CS implies that it is possible to reconstruct the sparse signal/image from incomplete data if some prior knowledge ...
This subsequently reduces the quality of the image, underscoring the need for image pre-processing. In this study, pre-processing was carried out to correct geometric and radiometric distortions incurred in the image scenes, as follows. 2.4.1. Geometric Correction Specifically, the image ...
Introduction In compressive sampling [1,2], we aim to estimate an image x0 ∈ Cn from m < n linear observations y ∈ Cm, y = Ax0, where A ∈ Cm×n is the measurement matrix. Since m < n, this problem is ill-posed. In order to solve this ill-posed problem, one needs some ...
The traditional TomoSAR building object height inversion algorithm is a fast Fourier transform, where the image is de-skewed, and then a fast Fourier transform is performed in the height direction to obtain the scatterer distribution in the height direction [2]. This algorithm requires a large ...