General linear image processing (GLIP) framework, which is based on abstract linear mathematics, opens a new way to the development of image processing techniques by providing specific operations and structures for image representation and processing. This paper presents different models proposed so far for general linear image processing, including the logarithmic image processing (LIP), the general adaptive neighborhood image processing (GANIP), the logarithmic adaptive neighborhood image processing (LANIP)ÿthe parameterized logarithmic image processing (PLIP), the homomorphic logarithmic image processing (HLIP) and the pseudo-logarithmic image processing (Pseudo-LIP). After a description of each approach, we focus on their distinctive theory issues. Several LIP-model based application examples are exposed and discussed in image filtering, edge detection and morphological operation to show the practical advantage of LIP model. This study is helpful for an appropriate use of existing general linear image processing approaches and for systematically designing new approach.