In this paper, a compression system with high synthetic architect is introduced, it is based on wavelet transform, polynomial representation and quadtree coding. The bio-orthogonal (tap 9/7) wavelet transform is used to decompose the image signal, and 2D polynomial representation is utilized to prune the existing high scale variation of image signal. Quantization with quadtree coding are followed by shift coding are applied to compress the detail band and the residue part of approximation subband. The test results indicate that the introduced system is simple and fast and it leads to better compression gain in comparison with the case of using first order polynomial approximation.
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.
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-
... Show MoreBACKGROUND: Color Vision Deficiency (CVD) is mostly an inherited trait and is not an uncommon problem. Prevalence of CVD differs among different ethnic and geographic properties of the population that affect their genetic constitution. Ishihara plates remain an internationally accepted tool for screening red-green CVD. OBJECTIVE: To determine the prevalence of red-green CVD among adult males from Baghdad province. PATIENTS AND METHODS: One thousand and five (1005) adult males were enrolled in this study, using a systematic sampling technique, and were screened for CVD utilizing 24-plate Ishihara plates and re-tested by EnChroma 39-Color plates. All males were residing in Baghdad and the center of Iraq. RESULTS: Among all tested males, 948 r
... Show MoreThe research aims:
1- To know the intemperance use of the internet by the University's students.
2- To know the differences with a statistical indication in the intemperance use of the internet after the gender's inconstant ( Males-females).
3- To know the differences with a statistical indication in the intemperance use of the internet after the Major's inconstant ( scientific- humanistic)
This current research restricts a sample of the university students for both sexes.
Theoretical frame:
The research viewed several theories that explains intemperance use of the internet & the results.
Research measures :
1- Research has been adapted the scale ( Internet use) which was prepared by the Moroccan researcher (
In this paper, a literature survey was introduced to study of enhancing the hazy images , because most of the images captured in outdoor images have low contrast, color distortion, and limited visual because the weather conditions such as haze and that leads to decrease the quality of images capture. This study is of great importance in many applications such as surveillance, detection, remote sensing, aerial image, recognition, radar, etc. The published researches on haze removal are divided into several divisions, some of which depend on enhancement the image, some of which depend on the physical model of deformation, and some of them depend on the number of images used and are divided into single-image and multiple images dehazing model
... Show MoreGroupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff
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