A contrast enhancement technique for low light images

Abstract

Digital Imagery systems are traditionally bad in low light conditions. In this paper, a new algorithm for contrast improvement is proposed. The algorithm consists of two stages. The first stage is decomposing the input image into four subbands by applying two-dimensional discrete wavelet transform and estimates the singular value matrix of sub band image. The second stage is that it reconstructs the enhanced image by applying the inverse DWT. The technique is compared with conventional image equalization technique such as standard General Histogram Equalization (GHE) and other state-of-the-art techniques such as Quadrant Dynamic Histogram Equalization (QDHE), Singular-Value-Wavelet based image Equalization (SVWE) and Singular Value Equalization (SVE) on the basis of their Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE) values. The simulation results indicated that the image contrast enhanced by the purposed method was higher than that of the images enhanced by the other conventional state-of-the-art techniques.