FuzzyCIE: fuzzy colour image enhancement for low-exposure images

Colour image enhancement not only is of high importance in consumer electronics, but also plays significant role in medical imaging, remotely sensed imaging, etc. Moreover, low-exposure colour images inherently lack sufficient image details which are exclusively necessary for workings in these domains. To address this less explored problem, a novel enhancement algorithm involving estimation of the fuzzy histogram with thresholding based on the computed effect of exposure value has been proposed. The algorithm operates on the lightness ( $$L^{*}$$ L ∗ ) component of the input image in $$L^{*}a^{*}b^{*}$$ L ∗ a ∗ b ∗ colour space, while preserving the colour-opponent dimensions ( $$a^{*} $$ a ∗ and $$ b^{*}$$ b ∗ ) to maintain the natural outlook of the image. This technique has been experimentally demonstrated over a dataset consisting of images generated at different exposure levels. Quantitative and qualitative analysis of the relative performance of the proposed algorithm has been shown with respect to state-of-the-art enhancement algorithms over the $$L^{*}a^{*}b^{*}$$ L ∗ a ∗ b ∗ space.