Performance Analysis of Histogram Equalization Methods for Low - Resolution Surveillance Face Images

Surveillance image enhancement methods frequently suffer from a number of drawbacks, including variable lighting conditions, noise, and low resolution making them more complex. Because of variable lighting conditions, images lose its details and artifacts may get introduced. To overcome these shortcomings and keeping significant features of the image, contrast enhancement methods such as Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE), Recursive Separated and Weighted Histogram Equalization (RSWHE), Dual Sub-Image Histogram Equalization (DSIHE), Recursive Sub-Image Histogram Equalization (RSIHE), Fuzzy Histogram Specification with Adaptive Brightness Preservation (FHSABP), Brightness Preserving Bi-Histogram Equalization (BBHE) and Brightness Preserving Histogram Equalization using Modified Entropy(BPHEME) are explored in this research work to study their impact on surveillance face images. The aim of our research is to identify the most effective HE methodology suitable for enhancement of CCTV images. By comparing the performance of these methods, we find that RSWHE perform well on surveillance face images.