Change detection captures the spatial changes from multi temporal satellite images due to
manmade or natural phenomenon. It is of great importance in remote sensing, monitoring …

Image enhancement (IE) technology can help enhance the brightness of remote-sensing
images to obtain better interpretation and visualization effects. Convolutional neural …

Deep learning technologies like convolutional neural networks have recently become
popular in the field of image denoising. A combined discrete wavelet transform (DWT) and …

This paper presents a convolutional neural network to automatically remove the haze
distribution using a single multispectral remote sensing image in the raw file format. To train …

An unmanned aerial system (UAS)-based imaging technology has gained great interests in
modern photogrammetry and remote sensing. However, due to the limitations of UAS …

For one geological model, multiple inversion results are usually obtained by inverted
different geophysical data. Comprehensive interpretation of multi-source geophysical data is …

In order to improve the visual effect of aerial images in foggy weather, a Retinex defogging
algorithm combining dark channel priors is proposed to solve the phenomenon of …

Photoacoustic imaging (PAI) is an emerging biomedical imaging modality, offering
numerous advantages, including high resolution and high contrast. In its application to brain …

In the realm of image denoising, the use of convolutional neural networks (CNNs) has lately
gained traction. Several activities involve the utilization of excellent-clarity pictures and …

In this paper, we propose an adaptive local thresholding method for roads segmentation
based on the normalization of HSV and Lab color models. The color normalization improves …