A nonlinear anisotropic diffusion equation for image restoration with forward-backward diffusivities

Background: In the image processing area, deblurring and denoising are the most challenging hurdles. The deblurring image by a spatially invariant kernel is a frequent problem in the field of image processing. Methods: For deblurring and denoising, the total variation (TV norm) and nonlinear anisotropic diffusion models are powerful tools. In this paper, nonlinear anisotropic diffusion models for image denoising and deblurring are proposed. The models are developed in the following manner: first multiplying the magnitude of the gradient in the anisotropic diffusion model, and then apply priori smoothness on the solution image by Gaussian smoothing kernel. Results: The finite difference method is used to discretize anisotropic diffusion models with forward-backward diffusivities. Conclusion: The results of the proposed model are given in terms of the improvement.

Lung Segmentation and Iterative Weighted Averaging Smoothing Technique on Chest Ct Images

Computed Tomography (CT) is one of the most commonly used imaging modalities for tumour detection and diagnosis, due to its high spatial resolution, fast imaging speed and wide availability. Nodules of the lungs and pathological residues with varied diameter can be comfortably viewed by computed tomography and can be categorized as benign or malignant. The key intention of this segmentation and smoothing is to develop an efficient methodology for an automated lung tumour diagnosis. Segmentation is the quantitative preprocessing step used in the chest CT analysis. The iterative weighted averaging technique is used in addressing the issues related to the segmentation and smoothing method employed in this paper. The methodology incorporates the accurate Lung Segmentation, enclosure of Juxtapleural nodules, the proper insertion of the bronchial vessels for enhancing the smoothness of the segmented Lung area. The steps involved in this paper include Image preprocessing by nonlinear anisotropic diffusion filtering, Thorax Extraction, Lung segmentation and iterative weighted averaging technique for smoothing the contours. The main feature in choosing the nonlinear anisotropic diffusion filtering is for properly preserving the regions unaffected with cancer and also to differentiate the artefacts involved due to the subject movements. In the fuzzy c- means clustering algorithm, the lung parenchyma is identified from the thorax region based on the fuzzy membership value and the affected regions are attached. The standard execution time for segmentation process of one dataset is 1.91s, it is the more rapid process than the manual segmentation.

Nonlinear anisotropic diffusion techniques for seismic signal enhancing - Carpathian Foredeep study

The use of nonlinear anisotropic diffusion algorithm for advanced seismic signal processing in the complicated geological region of Carpathian Foredeep was examined. This technique allows for an improvement of seismic data quality and for more accurate interpretation by the recovery of a significant amount of structural information in the form of a correlating seismic reflections and by preserving true DHI indicators. It also allows searching for more subtle geological structures. Anisotropic diffusion is an iterative image processing algorithm that removes noise by modifying the data by solving partial differential equations. Moreover, it can reduce image noise without blurring the edges between regions of different chrominance or brightness. This filter preserves edges, lines, or other features relevant to the seismic structural and stratigraphic interpretation. The algorithm also enables noise reduction without removing significant information from a seismic section even for high dips values. For a better estimation of anisotropic diffusion structure tensor, the parameterization is done using the depth field and the calculations in the two-way travel time field. The presented research shows the results of using an anisotropic diffusion algorithm for post-stack and migration processing of seismic 3D data collected in Carpathian reservoir rocks of southern Poland.