Huge number of medical images are generated and needs for more storage capacity and bandwidth for transferring over the networks. Hybrid DWT-DCT compression algorithm is applied to compress the medical images by exploiting the features of both techniques. Discrete Wavelet Transform (DWT) coding is applied to image YCbCr color model which decompose image bands into four subbands (LL, HL, LH and HH). The LL subband is transformed into low and high frequency components using Discrete Cosine Transform (DCT) to be quantize by scalar quantization that was applied on all image bands, the quantization parameters where reduced by half for the luminance band while it is the same for the chrominance bands to preserve the image quality, the zigzag scan is applied on the quantized coefficients and the output are encoded using DPCM, shift optimizer and shift coding for DC while adaptive RLE, shift optimizer then shift coding applied for AC, the other subbands; LH, HL and HH are compressed using the scalar quantization, Quadtree and shift optimizer then shift coding. In this paper, a new flipping block with an adaptive RLE is proposed and applied for image enhancement. After applying DCT system and scalar quantization, huge number of zeros produced with less number of other values, so an adaptive RLE is used to encode this RUN of zeros which results with more compression.Standard medical images are selected to be used as testing image materials such as CT-Scan, X-Ray, MRI these images are specially used for researches as a testing samples. The results showed high compression ratio with high quality reconstructed images
Objective: To assess the functional outcome, time to union, shoulder pain, blood loss, operative time, iatrogenic radial nerve injury, hospitalization, and infection. Methodology: It is a prospective randomized study on 30 patients with mid-shaft humerus fracture according to AO classification (1.2A1, 2, 3 and 1,2B) with functioning radial nerve. They were randomly dividing into two groups. Group A were treated by a closed antegrade interlocking nail, and group B treated by open reduction and locked compression plate fixation. The follow-up was up to 6 months, including time to union, shoulder pain, intraoperative blood loss, operative time and iatrogenic radial nerve injury. Functional outcome was assessed by quick DASH score. Resu
... Show MoreIn this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E1 , E2 , E3) of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the
... Show MoreThis paper present a simple and sensitive method for the determination of DL-Histidine using FIA-Chemiluminometric measurement resulted from oxidation of luminol molecule by hydrogen peroxide in alkaline medium in the presence of DL-Histidine. Using 70?l. sample linear plot with a coefficient of determination 95.79% for (5-60) mmol.L-1 while for a quadratic relation C.O.D = 96.44% for (5-80) mmol.L-1 and found that guadratic plot in more representative. Limit of detection was 31.93 ?g DL-Histidine (S/N = 3), repeatability of measurement was less that 5% (n=6). Positive and negative ion interferances was removed by using minicolume containing ion exchange resin located after injection valve position.
For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.
In this paper, we designed a new efficient stream cipher cryptosystem that depend on a chaotic map to encrypt (decrypt) different types of digital images. The designed encryption system passed all basic efficiency criteria (like Randomness, MSE, PSNR, Histogram Analysis, and Key Space) that were applied to the key extracted from the random generator as well as to the digital images after completing the encryption process.
The objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.
The database for this paper consists of night vision infrared images were taken by Zenmuse camera (FLIR Systems, Inc) attached on MATRIC100 drone in Karbala city. The experimental tests showed sign
Due to the continuous development in society and the multiplicity of customers' desires and their keeping pace with this development and their search for the quality and durability of the commodity that provides them with the best performance and that meets their needs and desires, all this has led to the consideration of quality as one of the competitive advantages that many industrial companies compete for and which are of interest to customers and are looking for. The research problem showed that the Diyala State Company for Electrical Industries relies on some simple methods and personal experience to monitor the quality of products and does not adopt scientific methods and modern programs. The aim of this research is to desi
... Show MoreWireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener
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