ABSTRACT
The human visual system has the capacity of instantaneously receiving a large amount of visual information about an abundance of details and numerous colors in a different dynamic range of light. To reproduce this is challenging since even the latest technology has limited abilities regarding the representation of the actual lighting. The HDR technology reproduces lightning rather faithfully. As a result, different techniques and software tools for creating HDR images are currently being developed. So far, combining LDR images of the same scene, taken with different exposition times, to produce an HDR image, has seemed to be the most reliable and the most common method in use. The area is in the early stages of development, so several software development companies are working on tools for the purpose of getting better and better results. Since neither a standardized method nor a possible candidate for a superior or even a preferable tool has emerged up to now, assessing the quality of HDR images created with each of the available and marketed tools appears to be an inevitability. The evaluation in this case is, nevertheless, a delicate matter, since the end user is the human eye, i.e., the very subjective human perception. To overcome this difficulty, both psychophysical and psychometrical experiments are extensively used. The study is aimed at analyzing the possibilities and the end results of the LDR-to-HDR procedure, using each of the leading software tools for creating HDR images. The goal is to contribute to the creation of standard methods and tools for creating images with high dynamic range.
REFERENCES
Abhishek, Rajput. (2010). High Dynamic Range Imaging.
Alessandro, Artusi., Thomas, Richter., Touradj, Ebrahimi., Rafal, Mantiuk. (2017). High Dynamic
Range Imaging Technology [Lecture Notes]. IEEE Signal Processing Magazine, 34(5):165-
172. doi: 10.1109/MSP.2017.2716957
Brooker, Jeffrey. (2020). High Dynamic Range Imaging.
Hongyi, Cai., TM, Chung. (2011). Improving the Quality of High Dynamic Range Images. Lighting
Research & Technology, 43(1):87-102. doi: 10.1177/1477153510371356
Mehlika, Inanici. (2006). Evaluation of High Dynamic Range Photography as a Luminance
Data Acquisition System. Lighting Research & Technology, 38(2):123-134. doi:
10.1191/1365782806LI164OA
Michael, Grossberg., Shree, K., Nayar. (2003). High Dynamic Range from Multiple Images: Which
Exposures to Combine?
Rafal, Mantiuk., Karol, Myszkowski., Hans-Peter, Seidel. (2015). High Dynamic Range Imaging.
doi: 10.1002/047134608X.W8265
Richard, Salisbury., Kenneth, Andrew, Hagan. (2014). High Dynamic Range Imaging.