Mobile Computational Photography

Mobile Computing Photography: Principles and Techniques for Mobile Photography offers a comprehensive exploration of the revolutionary field of computational imaging as applied to mobile devices. This book delves into how smartphone cameras, despite their inherent physical limitations compared to traditional cameras, leverage cutting-edge computational approaches to achieve stunning photographic and videographic results. Readers will gain a deep understanding of the core principles, algorithms, and applications that define modern mobile photography. Beginning with the evolution of digital imaging and the fundamental components of mobile camera systems—including image sensors (CCD vs. CMOS, size, resolution, shutter types) and the intricate Image Signal Processor (ISP)—the book then meticulously unpacks key computational photography techniques. Detailed chapters cover essential functions such as automatic focus, automatic white balance, and automatic exposure, exploring their underlying mechanisms and advancements in mobile contexts. The text further examines sophisticated features like High Dynamic Range (HDR) imaging, the complexities and opportunities of multi-camera computational photography, and robust video stabilization techniques. Finally, Mobile Computing Imaging ventures into advanced topics that are reshaping the landscape of mobile visual capture, including image/video bokeh effects, advanced low-light image and video processing, and super-resolution techniques. Crucially, it highlights the transformative impact of large models and artificial intelligence on enhancing mobile imaging capabilities, offering insights into deep learning-based ISP design. Written for scientists, researchers, practitioners, and postgraduates in computer vision, image processing, and mobile computing, this book serves as an indispensable resource for anyone seeking to master the intricacies and future trends of mobile computational photography.