In this study, an analysis of re-using the JPEG lossy algorithm on the quality of satellite imagery is presented. The standard JPEG compression algorithm is adopted and applied using Irfan view program, the rang of JPEG quality that used is 50-100.Depending on the calculated satellite image quality variation, the maximum number of the re-use of the JPEG lossy algorithm adopted in this study is 50 times. The image quality degradation to the JPEG quality factor and the number of re-use of the JPEG algorithm to store the satellite image is analyzed.

 The paper sheds light on the meanings of colours as a significant  medium reflecting the world linguistic image which represents the culture of any country since language is closely related with culture. Language goes hand in hand with people's daily expressions, specifically those cultural ones. Language is a way to store historical and cultural information, and is a means of transferring the experience of a group to outside groups. 

The world linguistic image identifies the standards of human behavior in dependence upon the human view of the surrounding world, along with the type of behavior with which the world interacts and to whose challenges and effects it responds. So, multi-cultural people perceive the sam

Mixed ligand complexes of bivalent metal ions, viz ; M= Co(II),Ni(II),Cu(II), Zn(II), Cd (II), and Hg(II) of the composition [M(Anth)2(TMP)] in 1:2:1 molar ratio, (where . AnthrH= Anthranilic acid (C7H7NO2) and Trimethoprime (TMP) = (C14H18N4O3) have been synthesized and characterized by repeated melting point determination, Solubility, Molar conductivity (Λm ),determination the percentage of the metal (M%) in the complexes by (AAS), FT-IR, magnetic susceptibility measurements [μeff (BM)] and electronic spectral data. The two ligands and their metal complexes have been screened for their bacterial activity against selected microbial strains (Gram +ve) & (Gram -ve).

Mixed ligand complexes of bivalent metal ions, viz ; M= Co(II),Ni(II),Cu(II), Zn(II), Cd (II), and Hg(II) of the composition [M(Anth)2(TMP)] in 1:2:1 molar ratio, (where . AnthrH= Anthranilic acid (C7H7NO2) and Trimethoprime (TMP) = (C14H18N4O3) have been synthesized and characterized by repeated melting point determination, Solubility, Molar conductivity (Λm ),determination the percentage of the metal (M%) in the complexes by (AAS), FT-IR, magnetic susceptibility measurements [µeff (BM)] and electronic spectral data. The two ligands and their metal complexes have been screened for their bacterial activity against selected microbial strains (Gram +ve) & (Gram -ve).

Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.