Image enhancement plays a crucial role in almost every image processing applications. The main aim of the image enhancement or correction is to improve the quality of the image by maximizing the information content in the given input image. The quality of the input image is improved by selecting the optimal parameter based on objective function during the optimization process through the global transformation function. So, the objective function plays an important role in the optimization process. In this context, this book presents a detailed study of different objective functions for image correction based popular bio and nature-inspired optimization algorithms such as Back Tracking Search (BSA), Improved Differential Search (IDS), Gaseous Brownian Motion Optimization (GBMO) and Wind Driven Optimization (WDO). The results obtained will clearly show qualitative and quantitative improvement. I hope this book is most helpful for the researchers and master¿s level students who are working in the area of optimization and digital image processing.