Single Image Contrast Enhancer Using Convolutional Neural Network and Bright Channel Prior
Publication Date : 14/03/2019
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Due to the poor lighting condition and limited dynamic range of digital imaging devices, the recorded images are often under or over exposed with low contrast. Most of previous single image contrast enhancement (SICE) methods adjust the tone curve to correct the contrast of an input image. Those method fail in revealing image details because of the limited information in a single image. In proposed convolutional neural network (CNN) is used to train a SICE enhancer and bright channel prior to enhance image. With the constructed data set, a CNN can be easily trained as the SICE enhancer to improve the contrast of an under-/over-exposure image. Experimental results demonstrate the advantages of our method over existing SICE methods with a significant margin.
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