Memorial Church image. HDR data courtesy of Paul Debevec.
If you're interested in capturing images and creating your first High Dynamic Range image then you are at the right place. I'll give an introduction into the subject with more specifics on how to build an easy and cheap imaging system and also the needed software to create your first High Dynamic Range image.
In photography and microscopy, dynamic range is a term used to describe the range of brightness levels from the darkest to the brightest parts of an image. The human eye can perceive a dynamic range of about 14 stops, while most cameras have a dynamic range of only 8-12 stops. This means that cameras struggle to capture all the details in an image, particularly in high-contrast scenes where the difference between the brightest and darkest areas is significant. However, there is a way to increase the dynamic range of natural scenes and microscopic images without having to spend a fortune on expensive equipment - by using a cheap and out-of-the-box hardware setup and software.
One such hardware setup that can be used to increase the dynamic range of images is a Raspberry Pi camera and a lens. The Raspberry Pi camera module is a small, lightweight camera that can be connected to a Raspberry Pi computer. It's a cost-effective solution that produces high-quality images and videos. The camera module can be purchased for as little as $25, and a compatible lens can be purchased for as little as $10. This makes it an affordable option for hobbyists and professionals alike.
To increase the dynamic range of the images captured by the Raspberry Pi camera, software can be used to combine multiple exposures into a single image. This process is known as High Dynamic Range (HDR) imaging. HDR imaging works by capturing several images of the same scene at different exposure levels and then merging them together to create a single image with a wider dynamic range. The software used for this process can be downloaded for free from the internet and can be installed on the Raspberry Pi computer.
One popular software that can be used for HDR imaging is OpenCV. OpenCV is an open-source computer vision library that can be used for a variety of image processing tasks, including HDR imaging. It has a Python interface that makes it easy to use and integrate into existing projects. The library also includes a number of tools for image manipulation, such as brightness and contrast adjustments, which can be useful for fine-tuning the final image.
Using a Raspberry Pi camera and OpenCV software, it's possible to capture high-quality images with a wider dynamic range than the camera would be capable of capturing on its own. This can be useful for a variety of applications, such as nature photography, astrophotography, and microscopy. For example, in microscopy, it's often necessary to capture images of cells or other samples that have a wide range of brightness levels. By using HDR imaging, it's possible to capture all the details in these samples, even in areas where the brightness levels are very different.
In conclusion, if you're looking for an affordable way to increase the dynamic range of your images, a Raspberry Pi camera and OpenCV software are an excellent choice. This cheap and out-of-the-box hardware setup can be used for a wide range of applications and can produce high-quality images with a wider dynamic range than the camera would be capable of capturing on its own. Whether you're a hobbyist or a professional, this setup is definitely worth considering. For a guide on which hardware and software you can easily build and use to create HDR images (or if you're in a hurry and just need already captured images from which you can create a nice HDR), have a look at my presentation on the subject here: https://github.com/johnmeshreki/hdr_rasberry.