Architectural Lighting Design: Image Processing and Analysis Software
Architectural lighting design is the field of work or study that is concerned with lighting buildings properly. To light a building properly, there are different requirements: the lighting should be visually pleasing, but it also needs to be well quantified to enable the building users to see properly while avoiding any type of discomfort. Glare is one such type of visual discomfort.
Glare can be quantified through a lighting measurement tool called a luminance camera. Unfortunately, a luminance camera is a very expensive piece of equipment that few lighting designers or researchers can afford. To overcome this problem, researchers developed a technique called High Dynamic Range Imaging (HDRI) that can quantify glare in a similar way that luminance cameras do, but using commercially available cameras (such as Canon/Nikon DSLR cameras, or even Raspberry Pi camera modules).
The HDRI technique requires several steps of image processing and analysis before a glare evaluation can be derived from the images. This project consists in developing an open-source and user-friendly desktop application that automates those image processing and analysis steps. The desktop app needs to be able to read a series of inputs (such as .jpg images and other text files), apply the image processing and analysis steps (which have been summarized in a publicly available written tutorial), and write the output file (which is going to be a .hdr image file). The app will build upon the image processing strengths of an existing open-source program (Radiance) and provide a Graphical User Interface for creating and analyzing HDR images. The app design should be user-friendly, intuitive, and flexible for the users.
Objectives
The main objective is to develop an open-source and user-friendly desktop application to create and analyze High Dynamic Range (HDR) images based on a series of inputs. HDR images are the lighting measurements used for glare quantification in architectural lighting design. Additional features could be added to the app if times allow; these can be discussed in due time.
The deliverables include a GitHub repository where the desktop application can be downloaded, together with installation instructions (if needed), and documentation about the app.
Motivations
The development of the High Dynamic Range Imaging (HDRI) technique means that hardware for glare quantification and glare research is now economically accessible for the majority of potential users. This first improvement was a huge step forward in enabling lighting designers and researchers to do their jobs better.
However, the HDRI technique still requires the application of several image processing and analysis steps. While a tutorial was recently published explaining all these steps, it is a tedious process and people who want to apply it need to have programming skills and some knowledge of Radiance (a command-line-based light calculation software). This can be directly observed by the number of posts on the Radiance online forum asking for help to use the HDRI technique.
Providing an open-source and user-friendly desktop application that automates all these steps would make glare quantification and glare research accessible for the majority of potential users. Such a second improvement would be the crowning stroke for glare quantification and research, and very much appreciated by the community. By enabling lighting designers and researchers to do their jobs better, it might also have an impact on how well buildings are lit, hence reducing discomfort and accidents (e.g., tripping or falling) due to glare.
Qualifications
Minimum Qualifications:
Basic front-end engineering/GUI development experience
Basic Git knowledge
Preferred Qualifications:UI/UX design experience
Windows, macOS, or Linux app development
Details
Project Partner:
Clotilde Pierson
NDA/IPA:No Agreement Required
Number Groups:2
Project Status:Accepting Applicants
Website:Link to a desktop application doing a similar job to what is asked in this project, but which does not follow the validated HDRI process: https://courses.washington.edu/hdrscope/index.html Link to the HDRI process tutorial: https://www.tandfonline.com/doi/full/10.1080/15502724.2019.1684319 Link to more information about HDRI: https://www.jaloxa.eu/webhdr/index.shtml
Video:
Link to a video showing a desktop application doing a similar job to what is asked in this project, but which does not follow the validated HDRI process: https://www.youtube.com/watch?v=ghPPDs7jXeE