Given a short query with keyphrases about a research idea in 2013 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: A study of image super-resolution for the SPIE conference on Mobile Computational Photography.

Keyphrases: image super-resolution images

Dataset description:
SUN360: The goal of the SUN360 panorama database is to provide academic researchers in computer vision, computer graphics and computational photography, cognition and neuroscience, human perception, machine learning and data mining, with a comprehensive collection of annotated panoramas covering 360x180-degree full view for a large variety of environmental scenes, places and the objects within. To build the core of the dataset, the authors download a huge number of high-resolution panorama images from the Internet, and group them into different place categories.
DIV2K: DIV2K is a popular single-image super-resolution dataset which contains 1,000 images with different scenes and is splitted to 800 for training, 100 for validation and 100 for testing. It was collected for NTIRE2017 and NTIRE2018 Super-Resolution Challenges in order to encourage research on image super-resolution with more realistic degradation.
Middlebury: The Middlebury Stereo dataset consists of high-resolution stereo sequences with complex geometry and pixel-accurate ground-truth disparity data. The ground-truth disparities are acquired using a novel technique that employs structured lighting and does not require the calibration of the light projectors.
BSD: BSD is a dataset used frequently for image denoising and super-resolution. Of the subdatasets, BSD100 is aclassical image dataset having 100 test images proposed by Martin et al..

Options:- A: SUN360  B: DIV2K  C: Middlebury  D: BSD
Middlebury