Increased interest in the subject of the image because of its great and growing link to the life of the individual and society and its impact on the overall political, economic and cultural conditions. This interest is no longer confined to the images of people or institutions, but has become beyond that to the images of countries and peoples and the impact on bilateral relations between them,

However, we find that the image of the Iraqi abroad remained vague and has not been scientifically recognized and the most that we can generalize are the features of the image of Arabs and Muslims abroad; and assume that the image of the Iraqi applies to them as the Iraqi is in the end an Arab or Muslim.

Based on this, the research

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

order to increase the level of security, as this system encrypts the secret image before sending it through the internet to the recipient (by the Blowfish method). As The Blowfish method is known for its efficient security; nevertheless, the encrypting time is long. In this research we try to apply the smoothing filter on the secret image which decreases its size and consequently the encrypting and decrypting time are decreased. The secret image is hidden after encrypting it into another image called the cover image, by the use of one of these two methods" Two-LSB" or" Hiding most bits in blue pixels". Eventually we compare the results of the two methods to determine which one is better to be used according to the PSNR measurs

In this paper solar radiation was studied over the Iraqi countary land. The best sun duration hours regions (maximum hours) in Iraq were estimated detected by using Geographic information system (GIS Ver. 9.2) program to apply the (Inverse distance weighting) IDW exact interpolation technique depending on the measured data of metrological stations were distributed on the land areas of Iraq. The total area of the best regions was calculated .Excel 2007 program is used in calculation, graphics and comparison the results.

    Today, Unmanned Aerial Vehicles (UAVs) or Drones are a valuable source of data on inspection, surveillance, mapping and 3D modelling matters. Drones can be considered as the new alternative of classic manned aerial photography due to their low cost and high spatial resolution. In this study, drones were used to study archaeological sites. The archaeological Nineveh site, which is a very famous site located in heart of the city of Mosul, in northern Iraq, was chosen. This site was the largest capital of the Assyrian Empire 3000 years ago. The site contains an external wall that includes many gates, most of which were destroyed when Daesh occupied the city in 2014. The local population of the city of Mosul has also large

The drainage basin's hydrological aspect studying is considered to be important issue because of their influence (especially in arid to semi-arid regions) on the water management projects, agricultural management projects, and grazing ones. The importance of this study is coming from the fact that AL-Dibdiba formation basin climate is arid to semi-arid and there are human activities (habitation and agricultural) in the east part of it, so the water resources management is needed for this basin. The morphometric analysis illustrates the hydrological aspects in a quantitative form; the problem is the use of the traditional schemes in the calculation processes (such as the topographic map and the planmeter), which coast time and money and a

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

In this paper, we have employed a computation of three technique to reduce the computational complexity and bit rate for compressed image. These techniques are bit plane coding based on two absolute values, vector quantization VQ technique using Cache codebook and Weber's low condition. The experimental results show that the proposed techniques achieve reduce the storage size of bit plane and low computational complexity.