Raw satellite images are considered high in resolution, especially multispectral images captured by remote sensing satellites. Hence, choosing the suitable compression technique for such images should be carefully considered, especially on-board small satellites, due to the limited resources. This paper presents an overview and classification of the major and state-of-the-art compression techniques utilized in most space missions launched during the last few decades, such as the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT)-based compression techniques. The pros and cons of the onboard compression methods are presented, giving their specifications and showing the differences among them to provide uni

Image combination is a technique that fuses two or more medical images taken with different conditions or imaging devices into a single image contain complete information. In this study relied on mathematical, statistical and spatial techniques, to fuse MRI images that captured horizontal and vertical times (T1, T2),  and applied a method of supervised classification based on the minimum distance before and after combination process, then examine the quality of the resulting image based on the statistical standards resulting from the analysis of edge analysis, showing the results to identify the best techniques adopted in combination process, determine the exact details in each class and between classes.

     This study investigates data set as satellite images of type multispectral Landsat-7, which are observed for AL_Nasiriya city, it is located in southern of Iraq, and situated along the banks of the Euphrates River. These raw data are thermal bands of satellite images, they are taken as thermal images. These images are processed and examined using ENVI 5.3 program. Consequently, the emitted Hydrocarbon is extracted, and the black body algorithm is employed. As well as, the raster calculations are performed using ArcGIS, where gas and oil features are sorted. The results are estimate and determine the oil and gas fields in the city. This study uncovers, and estimates several unexplored oil and gas fields. Whereas,

Deep Learning Techniques For Skull Stripping of Brain MR Images

     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include

In this study, a chaotic method is proposed that generates S-boxes similar to AES S-boxes with the help of a private key belonging to

In this study, dynamic encryption techniques are explored as an image cipher method to generate S-boxes similar to AES S-boxes with the help of a private key belonging to the user and enable images to be encrypted or decrypted using S-boxes. This study consists of two stages: the dynamic generation of the S-box method and the encryption-decryption method. S-boxes should have a non-linear structure, and for this reason, K/DSA (Knutt Durstenfeld Shuffle Algorithm), which is one of the pseudo-random techniques, is used to generate S-boxes dynamically. The biggest advantage of this approach is the produ

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-