Adopting Image Integration Techniques to Simulate Satellite Images

Abstract

Mathematical integration techniques rely on mathematical relationships such as addition, subtraction, division, and subtraction to merge images with different resolutions to achieve the best effect of the merger. In this study, a simulation is adopted to correct the geometric and radiometric distortion of satellite images based on mathematical integration techniques, including Brovey Transform (BT), Color Normalization Transform (CNT), and Multiplicative Model (MM). Also, interpolation methods, namely the nearest neighborhood, Bi-linear, and Bi-cubic were adapted to the images captured by an optical camera. The evaluation of images resulting from the integration process was performed using several types of measures; the first type depends on the determination of quality in the regions of the edges using a contrast measure as well as the number of edges and threshold. The second type is the global one that is based on the parameters of the image region, including the Mean (µ), Standard Deviation (SD), and Signal to Noise Ratio (SNR). The parameters also included the Amount of Information Added (AIA) to the original image, such as those for the total (AIAt) , edges (AIAe), and homogenous (AIAh) regions. The results showed the efficiency of the integration process in the image fusion with different resolutions in one image integrated resolution. The quality measures used were also capable in evaluating the most efficient techniques and determining the accurate information of the resulting image.

Feature Extraction in Six Blocks to Detect and Recognize English Numbers

“…It is encouraging to notice the matching in the outputs for both methods. The SVM algorithm is not presented within this paper because it is well known and presented online [21].…”

Quantitative Analysis of Blurry Color Image Fusion Techniques using Color Transform

“…It saves time and reduces costs by acquiring multiple images of the same scene or object. This can be particularly useful in applications such as medical imaging, where multiple scans can be expensive and time-consuming, object recognition, target tracking, image segmentation, remote sensing, and military reconnaissance, including remote sensing, air, environmental and military surveillance, robotics, and other fields [2]. In 2021, Ayodeji Salau et al [3] assessed the results of a fused image (white flower) using discrete wavelet transform (DWT) and discrete cosine transform (DCT) techniques.…”

Surface Plasmon Resonance (SPR) Simulation of a Gold-Bismuth Bi-layer Gas Sensor

“…Simulation is the study and construction of models or programs that adopt methods to approximate and imitate a physical or real life system to study the expected results of the system and its potential use in practical applications. The simulation system simulates a reality that is sometimes difficult to provide due to costs and human capabilities [3][4][5]. Therefore, the principle of plasmonic surface (SPR) frequency of the plasmonic surface (SPR) is used for this purpose, which occurs when the frequency of the incident ray equals the frequency of the wave of the plasmonic surface (SPW).…”