Digital Heritage Reconstruction Using Deep Learning-Based Super-Resolution Prathmesh R. Madhu and Manjunath V. Joshi 1 Introduction Heritage and archaeological sites across the world are a major source of information which acquaint us with our social history delineating the advancement of mankind. They are invaluable assets of cultural heritage. Such places serve as an excellent attraction for tourists which indirectly impacts the gross domestic product. This is one of the major reasons for government agencies globally for taking keen interest toward preserving these sites. Over a period of time, a number of natural calamities such as weathering, man-made hazards like pollution etc., have sabotaged these heritage sites. Fearing from any further damages to these sites by the tourists, access to many heritage sites is now restricted. One such example is the mandapa with musical pillars in Vithala temple at Hampi in India, where the visitors are not allowed to touch and experience the melodious sound from the musical pillars. A way to preserve the heritage sites is to physically renovate them. However, it requires a prolific amount of historical information in order to renovate them. It also poses a danger to the undamaged monuments and may fail to mimic the skill-full historical work. One may overcome the above problems by using restoration in digital domain An image can be acquired by sampling a continuous scene using a camera and the restoration can be carried out by using in-painting and super-resolution methods. In this work, we restrict our degradation in spatial domain only and propose a super- resolution approach for spatial resolution enhancement. When the sampling rate of the acquired scene is less than the Nyquist rate which is often the case with mobile cameras used by the tourists, it results in aliasing effect leading to distortion in the captured image. In addition to this, sensor point spread function and the motion of the camera introduce the blur that degrades the quality of the image being cap- tured. Image super-resolution is an algorithmic approach for increasing the spatial P. R. Madhu (B ) · M. V. Joshi Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India e-mail: prmadhu@daiict.ac.in M. V. Joshi e-mail: mv_joshi@daiict.ac.in © Springer Nature Singapore Pte Ltd. 2018 B. Chanda et al. (eds.), Heritage Preservation, https://doi.org/10.1007/978-981-10-7221-5_4 67