… Such image-specific curve can effectively perform mapping within a wide dynamic range. 3)
… training a deep image enhancement model in the absence of reference images through task-…

… image processing applications have emerged with promising performance. Learning-based
low-light image enhancement … joint pipeline of image enhancement and detection methods. …

… As for low-light image enhancement, we randomly sampled 100 images from MIT dataset
[2] and 50 testing image from LSRW dataset [9] for testing. We used two full-reference metrics …

… As far as we know, this is also the first trial in low-light image enhancement tasks. … Therefore,
inspired by the recent image enhancement methods based on the unpaired dataset, in the …

… To solve these two degradation issues, we present an underwater image enhancement
network via medium transmission-guided multi-color space embedding, called …

… The main difference between our method and existing multi-scale image processing
approaches is the way we aggregate contextual information. First, the existing methods [37, 71, 97] …

… ), our goal is to learn a mapping G : X → Y in order to perform automatic image enhancement.
We adopt a conditional GAN-based model where the generator tries to learn this mapping …

… and most detailed imaging study to date. The UKB imaging enhancement aims to perform
… making the UKB imaging enhancement by far the largest multi-modal imaging study in the …

… of imaging, resolution, and computational image processing that apply equally to the images
… forms of optical imaging with ever increasing clarity, particularly of biological specimens. …

… , and DL integrated with medical image processing techniques have also been explored …
to emphasize significant DL and image processing techniques proposed in the detection of …