access icon free Perceptually motivated enhancement method for non-uniformly illuminated images

Non-uniformly illuminated images often suffer from low visibility in dark areas. Traditional methods usually enhance non-uniformly illuminated images by bringing out the details in the dark areas, but easily result in over-enhancement. Motivated by the Weber contrast model, the authors propose a perceptually inspired image enhancement method, which treats an image as a product of a luminance mapping (LM) transfer function and a contrast measure (CM) transfer function. The contribution of this proposed method is two-fold. Firstly, they propose a progressive LM transfer function based on the sensitivity of the human visual system to emphasise changes at low brightness level and attenuates changes at high brightness levels. Secondly, they introduce a CM transfer function, which is based on a special implementation of a neural model of the human visual receptive field, to improve local intensity contrast. Experimental comparisons with some state-of-the-art methods show that the proposed method can achieve both contrast enhancement and visual fidelity preservation.

Inspec keywords: brightness; visibility; optical transfer function; image enhancement

Other keywords: luminance mapping transfer function; dark areas; perceptually motivated enhancement method; perceptually inspired image enhancement method; visual fidelity preservation; contrast enhancement; nonuniformly illuminated images; CM transfer function; Weber contrast model; low visibility; contrast measure transfer function; neural model; human visual system; LM transfer function

Subjects: Computer vision and image processing techniques; Optical, image and video signal processing

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