Contrast Enhancement using Completely Overlapped Uniformly Decrementing Sub-Block Histogram Equalization for Less Controlled IlluminationVariation

Illuminationpre-processingisaninevitablestepfor a real-time automatic face recognition system in solving challengesrelated to lighting variation for recognizing the face images. This paper proposes a novel framework namely Completely Overlapped Uniformly Decrementing Sub-Block Histogram Equalization (COUDSHE) to normalize or pre-process the illumination deficient images. COUDSHE is based on the idea that efficiency of the pre-processing technique mainly depends on the framework for application of the technique on the affected image. The primary goal of this paper is to bring out a new strategy for localizing a Global Histogram Equalization (GHE) Technique to help it adapt to the local light condition of the image. The Mean Squared Error(MSE), Histogram Flatness Measure, Absolute Mean Brightness Error(AMBE) are the objective measures used to analysis the efficiency of the technique.Experimental Results reveal that COUDSHE has better performance on Heavy shadow images and half lit image than the existing techniques.