Real world scenes have huge intensity variations which are not in the control of the capture process. While human eye has an excellent dynamic range that enables us to visualize precise contrast variations and dynamically adapts to illumination variations, the dynamic range of conventional imaging devices is limited because of the physical constraints of the sensors. As a result of limited capabilities of the sensors, image saturation is observed often when lighting conditions are unfavorable (very bright, dark or uneven). In such scenarios, the captured image will have some optimally illuminated parts while some parts may undergo saturation (underexposure or overexposure). This makes the captured scene visually unappealing and the capture suffers from significant information loss. In this work, we propose an imaging solution to recover the scene information lost due to saturation, and hence, produce a better quality image ensuring no or minimal saturation.