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Deep Visual Informatory Through Super-Resolution High Dynamic Range Imagery in Immersive Applications

EasyChair Preprint no. 7226

8 pagesDate: December 17, 2021

Abstract

Immersive environment has evolved into state-of-the-art applications ranging from multimedia and multimodal representations narrowing the boundaries of reality and the digital realm although perceived differently encompassing bits and pixels. While the visual quality of immersive representation is still being academically discussed, photography is the closest way of representing reality as it is and has the capacity to provide a prominent dimension of experience. Numerous efforts that require overcoming technical challenges, huge funding, and time had been done to imitate human vision using image sensors. Today's method in achieving high fidelity visuals is too dependent on hardware as opposed to the adaptation of techniques. This paper explores the use of photography techniques to capture images exceeding the capabilities of normal human vision which unveils a huge amount of information essential for immersive applications. The super-resolution image is necessary for revealing visual details while high dynamic range imaging deepens the details within details. The process involves image acquisition from case study sites, construction by computational image stitching, and the final communication output. The outcome will outline the challenges for further research and method used without full reliance on the capabilities of the hardware and its possible application in virtual heritage immersive applications.

Keyphrases: high dynamic range, Immersive Application, super-resolution

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:7226,
  author = {Muhammad Jafni Jusof and Nik Nabilah Izzati Juhari and Nurul Nasmira Shafie},
  title = {Deep Visual Informatory Through Super-Resolution High Dynamic Range Imagery in Immersive Applications},
  howpublished = {EasyChair Preprint no. 7226},

  year = {EasyChair, 2021}}
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