Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

An Overview of Image Enhancement Techniques


Affiliations
1 Shree Shankaracharya College of Engineering and Technology, Bhilai (CG), India
     

   Subscribe/Renew Journal


Retinex theory addresses the problem of separating the illumination from the reflectance in a given image and thereby compensating for non-uniform lighting. This is in general an ill-posed problem. In this paper we propose a variational model for the Retinex problem that unifies previous methods. Similar to previous algorithms, it assumes spatial smoothness of the illumination field. In addition, knowledge of the limited dynamic range of the reflectance is used as a constraint in the recovery process. A penalty term is also included, exploiting apriori knowledge of the nature of the reflectance image. The proposed formulation adopts a Bayesian view point of the estimation problem, which leads to an alge.braic regularization term that contributes to better conditioning of the reconstruction problem.

Keywords

Image Enhancement, Reflectance, Illumination, Visual System, Constancy, SSR, MSR, MSR-CR.
Subscription Login to verify subscription
User
Notifications
Font Size


Abstract Views: 209

PDF Views: 0




  • An Overview of Image Enhancement Techniques

Abstract Views: 209  |  PDF Views: 0

Authors

Manish Kumar
Shree Shankaracharya College of Engineering and Technology, Bhilai (CG), India
Chinmay Chandrakar
Shree Shankaracharya College of Engineering and Technology, Bhilai (CG), India

Abstract


Retinex theory addresses the problem of separating the illumination from the reflectance in a given image and thereby compensating for non-uniform lighting. This is in general an ill-posed problem. In this paper we propose a variational model for the Retinex problem that unifies previous methods. Similar to previous algorithms, it assumes spatial smoothness of the illumination field. In addition, knowledge of the limited dynamic range of the reflectance is used as a constraint in the recovery process. A penalty term is also included, exploiting apriori knowledge of the nature of the reflectance image. The proposed formulation adopts a Bayesian view point of the estimation problem, which leads to an alge.braic regularization term that contributes to better conditioning of the reconstruction problem.

Keywords


Image Enhancement, Reflectance, Illumination, Visual System, Constancy, SSR, MSR, MSR-CR.