Image Enhancement Based on Parameterized Logarithmic Image Processing

Abstract

Image enhancement techniques generally utilize linear arithmetic operations, however linear operations have obvious disadvantages to be improved. Parameterized logarithmic image processing (PLIP) model extends traditional logarithmic image processing (LIP) by adding several generalization parameters, yielding better enhancement results. In this thesis, we study the PLIP operations and their properties; implement several image enhancement methods based on the PLIP model, and evaluate their enhancement performance. Then we propose a new algorithm PLIP based for improving visual quality of medical image, we further evaluate its enhancement performance by comparing with several commonly used image enhancement methods and PLIP-based algorithms.