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- W4385067514 abstract "Image enhancement aims at improving the quality of an image for better visualization. Histogram equalization (HE) is an image enhancement technique based on image histogram modification and this algorithm flats the given image histogram and produces better result on the global scale but the HE technique shifts the mean brightness of original image. Rather than flattening the given histogram, matching the given image with some specified distribution might help to resolve the issue. However, when the goal is to extract information on the local scale, local enhancement techniques, e.g. local HE (LHE), contrast limited adaptive HE (CLAHE), are required. Although the local histogram modification techniques manage to extract local information, however, compromises the visual quality (e.g. over enhancement, shifts in mean brightness, etc.) of the image. In this paper, a novel technique called Local Histogram Matching with Normal Distribution (LHMND), is proposed to extract local information and enhance the image quality by taking advantage of the Normal histogram matching on the local scale. Experiment shows that our proposed method performs better in terms of preserving the mean brightness and contrast enhancement to some extent, in comparison with the relevant HE techniques, e.g. HE, LHE, and CLAHE." @default.
- W4385067514 created "2023-07-23" @default.
- W4385067514 creator A5083788507 @default.
- W4385067514 creator A5092516234 @default.
- W4385067514 date "2023-07-20" @default.
- W4385067514 modified "2023-09-30" @default.
- W4385067514 title "Image Enhancement using Local Histogram Matching with Normal Distribution" @default.
- W4385067514 doi "https://doi.org/10.36948/ijfmr.2023.v05i04.3807" @default.
- W4385067514 hasPublicationYear "2023" @default.
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