This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method

Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

Ultrasound has been used as a diagnostic modality for many intraocular diseases, due its safety, low cost, real time and wide availability. Unfortunately, ultrasound images suffer from speckle artifact that are tissue dependent. In this work, we will offer a method to reduce speckle noise and improve ultrasound image to raise the human diagnostic performance. This method combined undecimated wavelet transform with a wavelet coefficient mapping function: where UDWT used to eliminate the noise and a wavelet coefficient mapping function used to enhance the contrast of denoised images obtained from the first component. This methods can be used not only as a means for improving visual quality of medical images but also as a preprocessing

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

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

The object of this work is to investigate the effect of the addition of methanol on the shelf life and color characteristics of novolak resin. Different percentages were added and two mechanisms were suggested for the addition. High ortho structure (1, 2-3) novolak resin was prepared and used in the above investigation. Experimental determination using FT-IR and UV-spectroscopy showed that on the addition of 30% of methanol and according to the second mechanism of addition novolak shelf life increased to 12 months without obvious decomposition and color change. It is suggested that methanol plays an important role in the inhabitation of the reactive sites on the resin that are responsible for the oxidation of the polymer when exposed to

Background: The incidence of maternal mortality in
placenta previa accrete is 7%,and its preoperative
diagnosis is of a great value.
Objective: to evaluate the efficacy of transabdominal
color Doppler ultrasound in diagnosing placenta
previa accreta and inccreta. Color Doppler imaging
criteria used in: includes diffuse parenchymal
placental lacunar flow, focal intra parenchymal
placental lacunar flow and bladder uterine serosa
interphase hyper-vascularity.
Design: Prospective study on patients from
January2007 to January 2008.
Patients and method: 48patients with one caesarean
section or more and with persistent anterior placenta
previa diagnosed by transabdominal ultrasound were
examined by c

Background and Aim: The use of food dyes can cause certain diseases, such as anemia and indigestion, along with other disorders, tumors, and even cancer. Therefore, this study aimed to determine the chemical nature and toxicity of some commercial dyes locally used in processed foods compared with standard food dyes. Materials and Methods: Three types of standard and commercial food color additives (Sunset Yellow, Tartrazine, and Carmoisine) were extensively examined. The chemical structures and functional groups of the dyes were evaluated by Fourier-transform infrared (FTIR) spectroscopy. The melting temperatures of the dyes were also determined by chemical thermal analysis. The acute toxicity test to evaluate the standard and commercial