Set14s

Set14s is a benchmark dataset used in image processing, particularly for evaluating image super-resolution methods, though it is also employed for denoising, deblurring, and related tasks. It is commonly referenced as the Set14 collection and serves as a companion to other standard datasets in the field.

The set comprises 14 high-resolution images that cover a diverse range of content, including natural scenes, architectural structures, textures, and synthetic patterns. The images are used in their high-resolution form to generate standardized low-resolution inputs and to assess reconstruction quality across different content types.

In experimental practice, low-resolution images are created by downsampling the high-resolution references using a predefined kernel, typically a bicubic filter, and then algorithms attempt to reconstruct the original detail. Performance is usually reported with quantitative metrics such as PSNR and SSIM, across commonly used scale factors like 2x, 3x, and 4x. Some studies also report perceptual metrics or qualitative comparisons.

Historically, Set14s has been a widely cited benchmark in super-resolution research, offering more variety than Set5 while remaining smaller and easier to manage than larger datasets like BSD100 or Urban100. It provides a standard reference point for historical comparisons and benchmarking of new methods, contributing to reproducibility and cross-study comparisons.

Limitations of Set14s include its small size, which can lead to high variance in performance estimates, and its content may not fully reflect modern high-resolution imagery. Researchers often supplement it with larger or more up-to-date datasets to obtain a more comprehensive evaluation.