IEEE Trans Image Process - Content-aware dark image enhancement through channel division.

Tópicos

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Resumo

The current contrast enhancement algorithms occasionally result in artifacts, overenhancement, and unnatural effects in the processed images. These drawbacks increase for images taken under poor illumination conditions. In this paper, we propose a content-aware algorithm that enhances dark images, sharpens edges, reveals details in textured regions, and preserves the smoothness of flat regions. The algorithm produces an ad hoc transformation for each image, adapting the mapping functions to each image's characteristics to produce the maximum enhancement. We analyze the contrast of the image in the boundary and textured regions, and group the information with common characteristics. These groups model the relations within the image, from which we extract the transformation functions. The results are then adaptively mixed, by considering the human vision system characteristics, to boost the details in the image. Results show that the algorithm can automatically process a wide range of images-e.g., mixed shadow and bright areas, outdoor and indoor lighting, and face images-without introducing artifacts, which is an improvement over many existing methods.

Resumo Limpo

current contrast enhanc algorithm occasion result artifact overenhanc unnatur effect process imag drawback increas imag taken poor illumin condit paper propos contentawar algorithm enhanc dark imag sharpen edg reveal detail textur region preserv smooth flat region algorithm produc ad hoc transform imag adapt map function imag characterist produc maximum enhanc analyz contrast imag boundari textur region group inform common characterist group model relat within imag extract transform function result adapt mix consid human vision system characterist boost detail imag result show algorithm can automat process wide rang imageseg mix shadow bright area outdoor indoor light face imageswithout introduc artifact improv mani exist method

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