  As Part I of a paper series showcasing a new imaging framework, we consider
the recently proposed unconstrained Sparsity Averaging Reweighted Analysis
(uSARA) optimisation algorithm for wide-field, high-resolution, high-dynamic
range, monochromatic intensity imaging. We reconstruct images from real
radio-interferometric observations obtained with the Australian Square
Kilometre Array Pathfinder (ASKAP) and present these results in comparison to
the widely-used, state-of-the-art imager WSClean. Selected fields come from the
ASKAP Early Science and Evolutionary Map of the Universe (EMU) Pilot surveys
and contain several complex radio sources: the merging cluster system Abell
3391-95, the merging cluster SPT-CL 2023-5535, and many extended, or bent-tail,
radio galaxies, including the X-shaped radio galaxy PKS 2014-558 and the
``dancing ghosts'', known collectively as PKS 2130-538. The modern framework
behind uSARA utilises parallelisation and automation to solve for the w-effect
and efficiently compute the measurement operator, allowing for wide-field
reconstruction over the full field-of-view of individual ASKAP beams (up to 3.3
deg each). The precision capability of uSARA produces images with both
super-resolution and enhanced sensitivity to diffuse components, surpassing
traditional CLEAN algorithms which typically require a compromise between such
yields. Our resulting monochromatic uSARA-ASKAP images of the selected data
highlight both extended, diffuse emission and compact, filamentary emission at
very high resolution (up to 2.2 arcsec), revealing never-before-seen structure.
Here we present a validation of our uSARA-ASKAP images by comparing the
morphology of reconstructed sources, measurements of diffuse flux, and spectral
index maps with those obtained from images made with WSClean.
