A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.

Image Noise Removal on Heterogeneous CPU-GPU Configurations

A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. A comparison of the parallel implementation in multi-core, GPUs and a combination of both is performed. Performance has been evaluated in terms of execution time and Megapixels/second. We present several optimization strategies especially effective for the multi-core environment, and demonstrate significant performance improvements. The main advantage of the proposed noise removal methodology is its computational speed, which enables efficient filtering of color images in real-time applications.

Removal of 8-quinolinecarboxylic acid pesticide from aqueous solution by adsorption on activated montmorillonites

Sodium montmorillonite (Na-M), acidic montmorillonite (H-M), and organo-acidic montmorillonite (Org-H-M) were applied to remove the herbicide 8-quinolinecarboxylic acid (8-QCA). The montmorillonites containing adsorbed 8-QCA were investigated by transmission electron microscopy, FT-IR spectroscopy, X-ray diffraction analysis, X-ray fluorescence thermogravimetric analysis, and physical adsorption of gases. Experiments showed that the amount of adsorbed 8-QCA increased at lower pH, reaching a maximum at pH 2. The adsorption kinetics was found to follow the pseudo-second-order kinetic model. The Langmuir model provided the best correlation of experimental data for adsorption equilibria. The adsorption of 8-QCA decreased in the order Org-H-M > H-M > Na-M. Isotherms were also used to obtain the thermodynamic parameters. The negative values of ΔG indicated the spontaneous nature of the adsorption process.

Algerian natural montmorillonites for arsenic(III) removal in aqueous solution

The adsorption of As(III) from aqueous solutions using naturally occurring and modified Algerian montmorillonites has been investigated as a function of contact time, pH, and temperature. Kinetic studies reveal that uptake of As(III) ions is rapid within the first 3 h, and it slows down thereafter. Equilibrium studies show that As(III) shows the highest affinity toward acidic montmorillonite even at very low concentration of arsenic. The kinetics of As(III) adsorption on all montmorillonites used is well described by a pseudo-second-order chemical reaction model, which indicates that the adsorption process of these species is likely to be chemisorption. Adsorption isotherms of As(III) fitted the Langmuir and Freundlich isotherm models well. The adsorption of As(III) is pH-dependent obtaining an optimal adsorption at pH 5. From the thermodynamic parameters, it is concluded that the process is exothermic, spontaneous, and favorable. The results suggest that M1, M2, and acidic-M2 could be used as low-cost and effective filtering materials for removal of arsenic from water.

Removal of BrO3 − from drinking water samples using newly developed agricultural waste-based activated carbon and its determination by ultra-performance liquid chromatography-mass spectrometry

Activated carbon was prepared from date pits via chemical activation with H3PO4. The effects of activating agent concentration and activation temperature on the yield and surface area were studied. The optimal activated carbon was prepared at 450 °C using 55 % H3PO4. The prepared activated carbon was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, thermogravimetric-differential thermal analysis, and Brunauer, Emmett, and Teller (BET) surface area. The prepared date pit-based activated carbon (DAC) was used for the removal of bromate (BrO3 −). The concentration of BrO3 − was determined by ultra-performance liquid chromatography-mass tandem spectrometry (UPLC-MS/MS). The experimental equilibrium data for BrO3 − adsorption onto DAC was well fitted to the Langmuir isotherm model and showed maximum monolayer adsorption capacity of 25.64 mg g−1. The adsorption kinetics of BrO3 − adsorption was very well represented by the pseudo-first-order equation. The analytical application of DAC for the analysis of real water samples was studied with very promising results.