Guang Deng

TL;DR: An adaptive Gaussian filtering algorithm is proposed in which the filter variance is adapted to both the noise characteristics and the local variance of the signal.

TL;DR: The proposed generalized unsharp masking algorithm using the exploratory data model as a unified framework is designed to address three issues: simultaneously enhancing contrast and sharpness by means of individual treatment of the model component and the residual, reducing the halo effect by Means of an edge-preserving filter, and solving the out-of-range problem by mean of log-ratio and tangent operations.

TL;DR: A normalized complement transform has been proposed to simplify the analysis and the implementation of the LIP model-based algorithms and this new implementation has been compared with histogram equalization and Lee's original algorithm.

TL;DR: This paper proposes an efficient non-invertible transformation – the partial Hadamard transform to securely protect binary biometric representations in the design of cancelable biometrics and designs cancelable fingerprint templates that meet the requirements of revocability, diversity, non- invertibility and performance.

TL;DR: The logarithmic image processing (LIP) model is a mathematical framework which provides a specific set of algebraic and functional operations for the processing and analysis of intensity images valued in a bounded range that addresses the edge detection problem using the LIP-model based differentiation.