The anatomy of anisotropic diffusion filters

Comparing GPU Implementations of Bilateral and Anisotropic Diffusion Filters for 3D Biomedical Datasets

We compare the performance of hand-tuned CUDA implementations of bilateral and anisotropic diffusion filters for denoising 3D MRI datasets. Our tests sweep comparable parameters for the two filters and measure total runtime, memory bandwidth, computational throughput, and mean squared errors relative to a noiseless reference dataset.

Recursive Implementation of Anisotropic Filters

Gaussian filter is widely used for image smoothing but it is well known that this type of filters blur the image features (e.g., edges). Two extensions of Gaussian filters will be discussed in this survey. One is the anisotropic filtering (bilateral filtering or PDE-based anisotropic diffusion) for feature-preserving smoothing and the other is the recursive implementation of various filters tha...

Nonlinear Anisotropic Diffusion Filtering for Multiscale Edge Enhancement

Nonlinear anisotropic diffusion filtering is a procedure based on nonlinear evolution partial differential equations which seeks to improve images qualitatively by removing noise while preserving details and even enhancing edges. However, well known implementations are sensitive to parameters which are necessarily tuned to sharpen a narrow range of edge slopes; otherwise, edges are either blurr...

Nonlinear anisotropic diffusion filters for the numerical approximation of conservation laws

Anisotropic Diffusion Filtering with A-priori Estimated Orientation Field for Enhancing Low-quality Fingerprint Images

We present a novel combination of classic anisotropic diffusion filters, a-priori estimated orientation fields and a locally adaptive contrast enhancement step for improving the quality of fingerprint images. By applying our new approach to low-quality images of the FVC2004 fingerprint databases, we are able to show its equivalency to state-of-the-art enhancement methods for fingerprints. Linea...