The distortion, which occurs to the image often affects the existing amount of information, weakens its sharpness, decreases its contrast, thus leads to overlapping details of the various regions, and decreases image resolution. Test images are used to determine the image quality and ability of different visual systems, as we depended in our study on test image, half black and half white. Contrast was studied in the petition so as to propose several new methods for different contrasts in the edge of images where the results of technical differences would identify contrast image under different lighting conditions.

Steganography art is a technique for hiding information where the unsuspicious cover signal carrying the secret information. Good steganography technique must be includes the important criterions robustness, security, imperceptibility and capacity. The improving each one of these criterions is affects on the others, because of these criterions are overlapped each other.  In this work, a good high capacity audio steganography safely method has been proposed based on LSB random replacing of encrypted cover with encrypted message bits at random positions. The research also included a capacity studying for the audio file, speech or music, by safely manner to carrying secret images, so it is difficult for unauthorized persons to suspect

This research deals with process of artistic conception of nature's images between becoming and buration, as an attempt to transfer the philosophical concepts to art via it's structural applications in forming the picture, due to the importance of these concepts which might be engaged with the vision of the artist in his own and subjective contention with the nature. The research consists of four chapters, first one included the problem of the research, importance, need to the research and the aim of the research represented by process of artistic conception of nature's images between becoming  and buration. Also included the limits of research and most important terms. Second chapter included theoretical frame that consists of thre

In some cases, surgeons need to navigate through the computer system for reconfirmation patients’ details and unfortunately surgeons unable to manage both computer system and operation at the same time. In this paper we propose a solution for this problem especially designed for heart surgeon, by introducing voice activation system with 3D visualization of Angiographic images, 2D visualization of Echocardiography processed video and selected patient’s details. In this study, the processing, approximation of the 3D angiography and the visualization of the 2D echocardiography video with voice recognition control are the most challenging work. The work involve with predicting 3D coronary three from 2D angiography image and also image enhan

A sensitivity-turbidimetric method at (0-180^o) was used for detⁿ. of mebeverine in drugs by two solar cell and six source  with C.F.I.A.. The method was based on the formation  of  ion pair for the pinkish banana color  precipitate by the reaction of Mebeverine hydrochloride with Phosphotungstic acid. Turbidity was measured via the reflection of incident light that collides on the surface particles of   precipitated at 0-180^o. All variables were optimized. The linearity ranged of Mebeverine hydrochloride was 0.05-12.5mmol.L^-1, the L.D. (S/N= 3)(3S_B) was 521.92 ng/sample depending on dilution for the minimum concentration , with correlation coefficient r = 0.9966while was R.S.D%

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

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

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