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ijp-733
Wavelet compression for remotely sensed images
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Image compression is very important in reducing the costs of data storage transmission in relatively slow channels. Wavelet transform has received significant attention because their multiresolution decomposition that allows efficient image analysis. This paper attempts to give an understanding of the wavelet transform using two more popular examples for wavelet transform, Haar and Daubechies techniques, and make compression between their effects on the image compression.

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Publication Date
Thu Feb 01 2018
Journal Name
Iet Signal Processing
Signal compression and enhancement using a new orthogonal‐polynomial‐based discrete transform
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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Journal Of Science
Gray-Scale Image Compression Method Based on a Pixel-Based Adaptive Technique
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     Today in the digital realm, where images constitute the massive resource of the social media base but unfortunately suffer from two issues of size and transmission, compression is the ideal solution. Pixel base techniques are one of the modern spatially optimized modeling techniques of deterministic and probabilistic bases that imply mean, index, and residual. This paper introduces adaptive pixel-based coding techniques for the probabilistic part of a lossy scheme by incorporating the MMSA of the C321 base along with the utilization of the deterministic part losslessly. The tested results achieved higher size reduction performance compared to the traditional pixel-based techniques and the standard JPEG by about 40% and 50%,

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Publication Date
Fri Dec 24 2021
Journal Name
Journal Of Engineering Science And Technology. Journal Of Engineering Science And Technology
Grey-Level Image Compression Using 1-D Polynomial and Hybrid Encoding Techniques
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Publication Date
Tue Feb 24 2026
Journal Name
Baghdad Science Journal
EEG Lossless Signal Compression Based on Magnitude Classification and Run Length Encoding
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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
Experimental Evaluation of Thermal Performance of Solar Assisted Vapor Compression Heat Pump
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The thermal performance of indirect expansion solar assisted heat pump, IX-SAHP, was investigated experimentally under Iraqi climate. An Indirect-Solar Assisted Heat Pump system was designed, built, instrumented and tested. Experimental tests were conducted by varying the controlling parameters to investigate their effects on the thermal performance of the IX-SAHP such as cooling water flow rate, heating water flow rate, ambient temperature and solar radiation intensity. The investigation covered values of cooling water flow rate of (2, 3, 4, 5 l/min) and heating water flow rate of (2, 3, 4, 5 l/min) under meteorological condition of Baghdad from November 2014 to January 2015.

The results indicated that the performance of the IX-

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and Evaluation of Oral Disintegrating Tablets of Ketoprofen by Dirct Compression
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Ketoprofen is a non-steroidal anti-inflammatory (NSAID) drug with analgesic, anti-inflammatory, and antipyretic effects. It is widely used in the treatment of inflammation and pain associated with rheumatic disorders such as rheumatoid arthritis, osteoarthritis, and in soft tissue injury. The purpose of this study was to prepare an  oral disintegrating tablets of ketoprofen by simple method. The tablets were prepared by direct compression method and different ratios of various subliming agents or superdisintegrants were incorporated. Then these tablets were evaluated for hardness, friability, weight variation, water absorption ratio, disintegrating time and dissolution time. The results showed that Formula F11 batch had short disint

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Publication Date
Tue Dec 03 2013
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Detection and interpretation of clouds types using visible and infrared satellite images
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One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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