Enhancement of high dynamic range images using variational calculus regularizer with stochastic resonance

While capturing pictures by a simple camera in a scene with the presence of harsh or strong lighting like a full sunny day, we often find loss of highlight detail information (overexposure) in the bright regions and loss of shadow detail information (underexposure) in dark regions. In this manuscript, a classical method for retrieval of minute information from the high dynamic range image has been proposed. Our technique is based on variational calculus and dynamic stochastic resonance (DSR). We use a regularizer function, which has been added in order to optimise the correct estimation of the lost details from the overexposed or underexposed region of the image. We suppress the dynamic range of the luminance image by attenuating large gradient with the large magnitude and low gradient with low magnitude. At the same time, dynamic stochastic resonance (DSR) has been used to improve the underexposed region of the image. The experimental results of our proposed technique are capable of enhancing the quality of images in both overexposed and underexposed regions. The proposed technique is compared with most of the state-of-the-art techniques and it has been observed that the proposed technique is better or at most comparable to the existing techniques.