Computational photography is a field of image processing that uses computer algorithms to improve the quality of digital images. It was coined by Michael Abrash in 1999, and has seen a number of innovations since then.

Smartphones use computational photography to improve the quality of their images, and this has had a major impact on traditional mirrorless camera vendors. By incorporating techniques such as deep fusion, which combines multiple images to reduce noise and increase resolution, smartphones are able to produce high-quality images even in challenging lighting conditions.

Despite these advances, there are still some limitations to computational photography. One challenge is that it can be difficult for the software algorithms to account for all the possible variables in a given scene. This can lead to artifacts or other issues in the final image.

Another challenge is that computational photography techniques often require significant processing power, which can drain a device's battery quickly. As a result, many devices only use these techniques when necessary, such as in low-light conditions.

Nevertheless, computational photography has the potential to transform the way we capture and edit images, and it remains an exciting area of research and development in the field of image processing.

Keywords: computer algorithms, image processing, deep fusion, noise reduction, resolution enhancement, lighting conditions, processing power, artifact creation.