Author: Saif Kamil Shnain

Abstract: The computer vision branch of the artificial intelligence field is concerned with developing algorithms for analyzing image content. Data may be compressed by reducing the redundancy in the original data, but this makes the data have more errors. In this paper image compression based on a new method that has been created for image compression which is called Five Modulus Method (FMM). The new method consists of converting each pixel value in an (4×4, 8×8,16×16) block into a multiple of 5 for each of the R, G and B arrays. After that, the new values could be divided by 5 to get new values which are 6-bit length for each pixel and it is less in storage space than the original value which is 8-bits. Keywords: Compression, Astronomical image, FMM, block size.   Link: https://ijs.uobaghdad.edu.iq/index.php/eijs/article/view/7233

Abstract The object of the presented study was to monitor the changes that had happened in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To To fulfill this goal, different satellite images had been used in different times, MSS 1973, TM 1990, ETM+ 2000 and MODIS 2010. K-Means, which is unsupervised classification and Neural Net which is supervised classification, was used to classify the satellite images and finally, by using adaptive classification, which is applied supervised classification on the unsupervised classification. ENVI was used in this study. Keywords: Al-Hammar marsh , k-mean , Neural Net, ENVI Link :https://www.ijs.uobaghdad.edu.iq/index.php/eijs/article/view/9878