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

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

Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

The rivers are the main source of fresh water for many countries and the great development which is considered as one of the sustainable development elements in its various agricultural, industrial, domestic and environmental fields .The countries of the world seek food security and water security in order to ensure the basic needs of citizens .Because their distribution is uneven in many regions of the world with different human needs, which leads to conflicts over water sources, especially those located in one international river basin .This has led to the emergence of internationallegal rules governing the management of The problem revolves around the dialectic between limited water resources and increased need for water use b

Effect of nano and micro SiO2 particles with different weight percent (2,4,6,8 and 10) %wt on the Interlaminar fracture toughness (GIc) of 16-plies of woven roving glass fiber /epoxy composites prepared by hand lay – up technique were investigated. The specimens were tested using DCB test (mode I).
Area method was used to compute the interlaminar fracture toughness. The results show that, GIc would increase with the increasing in the filler content, the main failure in microcomposites and nanocomposites was delamination in the layers, the delamination reduced with increasing in the filler content.